A PERCEIVED VALUE FRAMEWORK FOR EXPLAINING
PATIENTS' INTENTIONS TO USE
PHARMACEUTICAL CARE SERVICES
■■ ^- . ,'\ <
DAVID PAUL NAU
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
:, .. ; '> K;* ' , V ?
David Paul Nau
This dissertation is dedicated to my parents, Paul and Mary Lou Nau, for teaching
me to work hard, set high standards and never stop learning. Their steadfast support has
helped me go far beyond what I once thought possible.
People are rarely successful without the help of family, friends and colleagues.
My success has been due to the support of many people. Most importantly, my parents
provided me with the values and discipline necessary for success. My brother. Bill, and
friends, Mike, Joe and Michelle, provided encouragement and relaxation when needed
most. Martha, my fiance and friend, has shown me love and helped me understand
myself. She, along with Jena and Paige, have taught me about the truly important things
I must also acknowledge the influence of numerous teachers and mentors. Karen
Kier at Ohio Northern University encouraged me to pursue graduate education and Chuck
Hicks at the University of Toledo gave me the opportunity to work towards a master's
degree. Jim Klepcyk and Bill Owad at The Toledo Hospital taught me the basics of
management and helped me refine my writing and organizational skills, while Bob
Williams, Peter lafrate and Alan Knudsen gave me the opportunity to apply those skills at
Shands Hospital. My many thanks also to B.T. Lively and Monica Holiday for building
my confidence at teaching. ^ > f ; ^ , *
The last four years have been influenced by numerous faculty in the University of
Florida College of Pharmacy. Rich Segal helped me enroll in the graduate program that
has given me so much. Special thanks go to Doug Ried and Earlene Lipowski for their
advice, friendship and confidence in me. My gratitude goes to all members of the
Therapeutic Outcomes Monitoring group who provided me with numerous opportunities
to excel and who treated me as their colleague, to Carole Kimberlin and Jane Pendergast
for their research advice and service on my dissertation committee, and to all other faculty
in the Department of Pharmacy Health Care Administration. Lastly, heartfelt thanks go
to all of my fellow graduate students who provided friendship, encouragement and many
'? ^-«.J■ ■' .'•«-:>„/ ?5
TABLE OF CONTENTS
CHAPTERS , . ,.
1 INTRODUCTION 1
The Need for the Study 1
Problem Statement 8
Purpose and Significance 10
Research Questions 1 1
2 REVIEW OF LITERATURE 12
Perceived Quality and Value 18
Health Beliefs 27
Synthesis of Paradigms 33
3 RATIONALE AND THEORETICAL FRAMEWORK 39
Theoretical Framework 43
4 METHODS 46
Sample Selection 46
Data Collection Procedures 47
Study Variables 47
Instrument Development and Validation 52
Data Analysis 55
5 RESULTS '... 65
Endogenous Variables 67
Miscellaneous Questions 70
Construct Validity 71
Path Analysis 75
6 DISCUSSION 87
Review of Study Objectives 87
Discussion of Results 89
Implications for Pharmacy Practice 96
A QUESTIONNAIRE 115
B ALTERNATIVE MODELS 120
C INTER-ITEM AND ITEM-TO-TOTAL CORRELATIONS .... 123
D SUBJECTS' COMMENTS ON CLINIC SERVICES 124
BIOGRAPHICAL SKETCH 128
Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
A PERCEIVED VALUE FRAMEWORK FOR EXPLAINING
PATIENTS' INTENTIONS TO USE
PHARMACEUTICAL CARE SERVICES
David Paul Nau
Chairman: L. Douglas Ried, Ph.D.
Department: Pharmacy Health Care Administration
The purpose of this study was to investigate how patients' perceptions of the
benefits, costs and value of pharmaceutical care collectively influence their intentions
to use a pharmaceutical care service. Additionally, the extent to which the perceived
threat of a specific health problem affects patients' perceptions of the benefits of
pharmaceutical care was examined. A "Perceived Value Model for Explaining
Patients' Intentions to Participate in Pharmaceutical Care" was developed. Within
this model, the perceived value of pharmaceutical care service is conceptualized as
being a tradeoff between the perceived benefits and perceived costs of using the
pharmaceutical care service, wherein the perceived benefits represent a perceived
reduction in a specific health threat and the perceived costs represent the time and
emotional costs associated with using the service. The perceived benefits of using the
service, in turn, are influenced by patients' perceptions of the extent to which they are
threatened by the health problem that the service is designed to prevent or alleviate.
The model was evaluated with survey data collected from 154 patients who
were enrolled in a pharmacist-run anticoagulation clinic. The model did not exhibit
adequate goodness of fit with the data. However, the goodness of fit was improved
significantly by revising the model to include the influence of perceived benefits on
the perceived costs of the service. This model exhibits good fit with the data (chi-
square/degrees of freedom ratio = 2.37, TLI = 0.99 and AIC - 57.31) and explains
68% of the variance in the subjects' intentions to use the pharmaceutical care service.
Hence, the extent to which a pharmaceutical care service is perceived to
reduce the likelihood of experiencing a health problem (i.e., perceived benefits) has a
direct, positive effect on peoples' perceptions of the value of the pharmaceutical care
service, as well as an indirect effect on perceived value by its influence on the
perceived costs of the service. The perceived benefits and perceived costs of using a
pharmaceutical care service greatly influence the perceived value of the service,
which in turn influences peoples' intentions to use the service.
^ ' \l fl
' Need for the Study
The Problem of Drug-Related Morbidity
Drugs are powerful therapeutic tools; however, their inappropriate use can lead to
unresolved health problems or iatrogenic injury. The failure of a therapeutic agent to
produce the intended therapeutic outcome is termed drug-related morbidity (Hepler and
Strand, 1990). This concept includes both treatment failure and the production of new
medical problems. If untreated, drug-related morbidity may result in drug-related
mortality. Johnson and Bootman (1995) estimated the annual cost of managing drug-
related morbidity and mortality in the United States to be $76 billion.
Drug-related morbidity is often preceded by a drug-related problem. A drug-
related problem (DRP) is an event or circumstance involving drug treatment that actually
or potentially interferes with the patient's experiencing an optimum outcome of medical
care (Hepler and Strand, 1990). Strand et al. (1990) delineated eight categories of drug-
related problems: „.'■.■ :-' ..' • ' •
1. Untreated Indication. The patient is in need of drug therapy but is not
receiving it. .\ri ? ^^- ^^ ' i. . L*
2. Improper Drug Selection. The wrong drug is being used to treat the
3. Subtherapeutic Dosage. Too little of the correct drug is being used.
4. Failure to Receive Drug. The patient does not receive the drug due to
noncompliance, an inability to pay for the drug, or an inadequate drug distribution
5. Overdosage. Thepatient receives too much of the correct drug.
6. Adverse Drug Reaction. This is an unintended or potentially harmful effect
of a drug. "' f ^ t >
7. Drug Interaction. The patient experiences a medical problem as the result of
a drug-drug, drug-food, or drug-laboratory interaction.
8. Drug Use without Indication. The patient is taking a drug for which he/she
has no medical need.
These problems may arise due to inappropriate prescribing, inappropriate delivery
of the drug, inappropriate behavior by the patient, inappropriate monitoring, or patient
idiosyncracy. Although patient idiosyncracy is inherently unpreventable, most of the
other types of DRPs can be prevented (Hepler and Strand, 1990; Strand et al., 1990;
The incidence of preventable drug-related morbidity and mortality is uncertain.
Studies typcially have shown drug-related problems to being accountable for about 3-19%
of hospitalizations (Caranasos, Stewart and Cluff, 1974; Leape et al., 1993; Grymonpre et
al., 1988). While many adverse drug-related events are due to unpredictable adverse drug
reactions, a significant portion are due to noncompliance, treatment failures or medication
errors (Leape et al., 1993; Grymonpre et al., 1988; McKenney and Harrison, 1976;
Sullivan et al.,1990). A retrospective study of asthma mortality found that more than half
of these deaths could have been prevented through better drug use (Fletcher et al., 1990).
While these studies examined the influence of particular types of drug-related problems
in varying ways, only one study has attempted to estimate the incidence of drug-related
morbidity and mortality using Hepler and Strand's definition of drug-related problems
(Johnson and Bootman, 1995). An expert panel in this study estimated that under the
traditional medication-use system, less than 60% of patients receiving medication would
achieve optimal therapeutic outcomes (i.e., the absence of DRPs); the remainder
experience a treatment failure and/or a new medical problem. The panel also suggested
that about half of these drug-related problems could be prevented through changes in the
Preventability implies that methods for averting a problem are known and that the
problem results from failure to apply that knowledge (Leape et al., 1993). Although most
health professionals possess knowledge essential to the prevention of drug-related
problems, the traditional system for the prescribing, dispensing and consuming drugs
does not encourage the appropriate application of this knowledge (Hepler and Grainger-
Rousseau, 1995). Several authors have suggested that the traditional medication-use
system is in need of an overhaul (Manasse, 1989; Hutchinson and Hatoum, 1990) and still
others have suggested that a shift towards pharmaceutical care can improve the
medication-use system (Hepler and Strand, 1990; Hepler and Grainger-Rousseau, 1995).
Pharmaceutical care is the responsible provision of drug therapy for the purpose of
achieving definite outcomes that improve a patient's quality of life (Hepler and Strand,
1990). One of the key differences between a pharmaceutical care system and the
traditional medication-use system is the presence of a feedback loop through which
clinicians can monitor the impact of drug-therapy on the patient's health and make
necessary corrections to ensure that optimal outcomes are achieved. Thus, the three
essential functions of a pharmaceutical care system are initiating therapy, monitoring
therapy, and managing (correcting) therapy (Hepler and Grainger-Rousseau, 1995).
Another key difference between these two systems is that the pharmaceutical care
system is built on a team approach to care with shared responsibility for a patient's
outcomes. Hepler and Grainger-Rousseau (1995) suggest that pharmacists can play an
essential role in the pharmaceutical care system by collaborating with physicians to
monitor and manage patients' therapeutic outcomes . Grainger-Rousseau et al. (1997)
designed a Therapeutic Outcomes Monitoring (TOM) system for pharmacists based upon
the following principles:
1 . Cooperation among physicians, pharmacists, and patients in managing drug
therapy requires an explicit (communicable) structure of functions, relationships
and responsibilities to clarity expectations. Pharmacists' "membership" on a
primary care team requires that they perform a set of core tasks, shared authority
and responsibility, and have access to information.
2. Monitoring and managing drug therapy should be the pharmacist's principal
3. Therapeutic monitoring is practical for all competent pharmacists.
4. Changes in the organization and relationships of pharmacy practice may be
more important initially than extensive re-education of pharmacists in
5. A disease-oriented implementation strategy may allow pharmacists to target
high-risk patients in their practices, simplify training and allow phased
implementation of pharmaceutical care.
6. Managing whole patients to improve patients' quality of life requires
management of all aspects of therapy, not merely therapy for specific diseases.
7. Systematic performance evaluations are required to maintain full
The core tasks of a TOM pharmacist include 1) the education of patients on their
disease, the role of the medications in controlling their disease, the proper use of their
medications, and monitoring strategies; 2) the regular and continual monitoring of
patients' disease-control and/or drug-related problem resolution; and, 3) consultation with
physicians regarding changes to patients' drug-therapy . Whereas the education of the
patient can be accomplished in one or two sessions, the monitoring of the patient requires
the pharmacist and patient to communicate on a regular basis, usually monthly.
Following each interaction, the pharmacist documents key indicators of the patient's
control of his or her disease and provides a report to the physician.
Research is currently being conducted to determine the impact of TOM services
on the incidence of drug-related morbidity among persons with asthma. These services
are provided by specially trained pharmacists in community pharmacies around north-
central Florida in conjunction with the physicians of AvMed Health Plan (an IPA-model
health maintainence organization) . It is hoped that patients who participate in this
collaborative system of care will experience a lower incidence of drug-related morbidity
as evidenced by fewer emergency center visits and hospitalizations.
Although this research suggests that the TOM approach to enacting
pharmaceutical care holds promise, a number of problems have been identified. A major
problem has been the sub-optimal participation rate by patients. Very few patients have
interacted with the TOM pharmacists on a regular basis over a period of one year.
Anecdotal reports from pharmaceutical care projects around the nation have suggested
similar problems with patient participation. This is of serious concern since the ability of
the TOM services to facilitate a reduction in drug-related morbidity is heavily dependent
upon the active participation of patients. ■
Suboptimal patient participation in pharmaceutical care
Therapeutic Outcomes Monitoring services can only be successful when patients
are active participants. Although interviews with asthma patients during the formative
stages of the TOM project suggested that patients would like the services, experiences
with the implementation of these services have been less encouraging. Research by this
author found that only 26 out of 71 patients (37%) who were offered the opportunity to
participate in TOM services agreed to participate, and only 2 asthma patients out of the
aforementioned 26 actually met with their pharmacist on a regular basis over the course
of one-year. Unstructured telephone interviews and anecdotal reports from the TOM
pharmacists suggested that many patients did not perceive the benefits of regular
interaction with the pharmacist as sufficient to warrant their continued participation (e.g.,
"I don't think I am getting enough out of it to make it worth my while").
Tomeko and Strand (1995) reported that 25% of patients who participated in the
Minnesota Comprehensive Pharmaceutical Care project were immediately appreciative of
pharmaceutical care and became actively involved; another 65% required more time and
experience with the service to fully "appreciate if; while another 5-10%) never actively
participated in the services. This pattern suggests that most patients do not immediately
understand the potential benefits or value of participation in pharmaceutical care. This
may be due to a lack of experience with pharmaceutical care in community pharmacies.
Findings by Nau, Ried and Lipowski (1997) show that relatively few patients have
experienced pharmaceutical care. They surveyed 198 asthmatics in Florida and found
that 31.3% of these patients received a basic level of outcomes monitoring services from
their pharmacists and only 6.1%) reported participating in comprehensive pharmaceutical
care. Boulding, Kalra and Staelin (1995) found that expectations for future service
encounters are based upon persons' past experience with that service, and Schommer
(1997) found that patients' expectations for medication-counseling were related to their
past experience with medication-counseling. Hence, the low level of pharmaceutical care
in pharmacies encourages low expectations for future encounters with the pharmacist.
Patients typically expect their pharmacist to answer questions when necessary
(Schommer, 1996), but may view offers of pharmaceutical care services as unusual and
unnecessary (e.g., "If no one offered this service before, it must not be that important").
Therapeutic Outcome Monitoring services were developed to facilitate the
transition of the traditional medication-use system to pharmaceutical care. Pharmacists
who provide TOM services in collaboration with physicians could decrease the
prevalence of drug-related morbidity and enhance the quality of life of patients with
chronic diseases. However, the attainment of this goal has been hampered by sub-optimal
participation by patients. Although one could argue that the low participation rate is due
to the failure of pharmacists to adequately communicate the potential benefits of TOM
services, the extent to which the perceived benefits of TOM services influences a
patient's decision to regularly participate is unknown. A better understanding of patients'
decisions regarding participation in TOM services may facilitate the implementation of
pharmaceutical care thereby reducing the prevalence of drug-related morbidity.
As indicated by the previous discussion, the extent to which our society is able to
realize a reduction in the prevalence of drug-related morbidity and mortality is partly
dependent upon the active participation of patients in pharmaceutical care. Yet, very little
is known about patients' decision-making processes regarding participation in
pharmaceutical care. It is apparent that the concept of pharmaceutical care is new to most
patients and that they may not readily accept or expect this new approach to care. If they
do not believe they will benefit by participating in care, they are unlikely to participate.
To date, no one has throroughly examined patients' perceptions of the benefits of
Additionally, there may be significant barriers to participating in pharmaceutical
care. The time involved in interacting with the pharmacist or the monetary costs of
receiving TOM services may preclude regular involvement. Experiences from the TOM
project at the University of Florida suggest that some patients find the regular meetings
with the pharmacist to be inconvenient or too frequent. Yet, the extent to which patient
participation in pharmaceutical care is influenced by monetary or nonmonetary costs is
In previous work regarding patients' perceptions of pharmacists' helpfulness, one
group of authors (Nau, Ried and Lipowski, 1996) has suggested that the perceived value
of a pharmaceutical care service will be predictive of its utilization. They conceptualized
the perceived value of a pharmaceutical care service as the ratio of the perceived benefits
to perceived costs of participation in that service. According to this conceptualization,
increasing the perceived benefits or decreasing the perceived costs of the service will
enhance its utilization. While there are numerous models of consumer behavior and
health service utilization consistent with this conceptualization (Dodds and Monroe,
1985; Ronis, 1992; Rosenstock, 1966; Wood and Scheer, 1996; Zeithaml, 1988) the
predictive validity of this conceptualization has not been determined.
Very little work has been published regarding patients' perceptions of the benefits,
costs, or value of pharmaceutical care (Chewning and Sleath, 1996; Hartman and Im,
1992; Nau, Ried and Lipowski, 1996). Since relatively few formalized pharmaceutical
care services are in existence, no one has thoroughly studied past or current participants
in pharmaceutical care to determine the relationship of their perceptions of benefits, costs
and value to their intentions to continue participation. Additionally, no one knows the
determinants of the perceived benefits of pharmaceutical care. This dearth of knowledge
has spurred the American Pharmaceutical Association to conduct a national survey of the
public's perception of the potential benefits and value of pharmaceutical care. A better
understanding of this relationship may facilitate a more effective transition to
^ Purpose and Significance
The overall goal of this research is to assess patients' perceptions of the benefits,
costs, and value of pharmaceutical care, and to determine whether these perceptions are
predictive of their intentions to regularly participate in pharmaceutical care. Yet another
purpose is to determine whether patients' perceptions of the benefits or value of
pharmaceutical care are influenced by their perceptions of their susceptibility to specific
health problems. This should provide a better understanding of the relationship between
patients' perceptions of their health, the perceived benefits and costs of pharmaceutical
care and their willingness to utilize pharmaceutical care services. This knowledge will be
useful in developing promotional strategies aimed at increasing patients' use of
pharmaceutical care services.
This research may also help pharmacists understand how their patients would like
the pharmaceutical care services structured. For example, it may be determined that
patients prefer more flexibility in appointment times or prefer not to have appointments.
Structuring the services consistent with patient preferences may enhance participation.
By increasing the use of pharmaceutical care services, health care providers will
be better able to identify, resolve and prevent drug-related problems. In turn, this should
enhance the health status of persons with chronic illnesses and decrease the estimated $76
billion spent annually on drug-related morbidity and mortality (Johnson and Bootman,
1995). __.'■:,"■ I -
In meeting the goals of this project, the following questions will be addressed:
1 ) What are the relationships among the perceived benefits, perceived costs and
perceived value of pharmaceutical care?
2) What is the relationship of each of these perceptions to patients' intentions to
participate in pharmaceutical care?
3) Do patients' perceptions of their vulnerability to a specific health threat
influence their perceptions of the benefits of pharmaceutical care?
This literature review will focus on three paradigms for explaining patients' use of
health care services: satisfaction, perceived quality and value, and health beliefs.
The health care professions have typically relied upon patient satisfaction as the
primary predictor of patients' use of health care services. This approach has been
championed by John Ware and colleagues over the past twenty years (e.g.. Ware, Davies-
Avery and Stewart, 1978) whose work has sought to improve the validity and reliability
of patient satisfaction measurement. However, the progression of Ware's research has
been different than that of the satisfaction research in the field of marketing. Whereas
Ware began with the measurement of satisfaction and then sought to strengthen the
theoretical underpinnings of satisfaction responses, the marketing researchers spent a
great deal of time establishing the theoretical basis for satisfaction and then moved
towards the development of valid measures of this construct.
Most marketing researchers support a disconfirmation of expectations paradigm
for satisfaction (Oliver, 1 980). In this paradigm, a consumer will be satisfied when the
service level meets or exceeds his or her expectations for performance (i.e., positive
disconfirmation) and will be dissatisfied when the service level does not meet those
expectations (i.e., negative disconfirmation). Hence, consumers' satisfaction is
dependent upon their expectations and the performance of the service provider. Because
consumer expectations may vary, the same level of performance may produce differing
levels of satisfaction.
Regardless of any variation between individuals in their expectations, it is
assumed that a person's satisfaction with a service will predict their subsequent behavior.
In health care, the behaviors (or behavioral intentions) most studied in relationship to
satisfaction have been adherence to medication regimens or clinic appointments and the
willingness to use a particular provider or service (Ware, Davies-Avery and Stewart,
1978). Examples of these relationships are presented in the following paragraphs.
Haynes (1976) concluded in a literature review that a significant positive
relationship exists between adherence and a patient's satisfaction with specific
components of medical care. A more recent study by Sherboume et al. (1992) found
adherence to medical advice on diet and exercise was positively correlated to satisfaction
with the interpersonal aspects of care (r=0.23), but negatively correlated to satisfaction
with the technical quality of care (r=-0.15). A study by Stanton (1986) found no
relationship between antihypertensive medication adherence and satisfaction with the
Satisfaction was also related to clinic appointment keeping in Korsch et al. (1968),
and Pearce, O'Shea and Wesson (1979). Studies by Becker, Drachman and Kirsht
(1974); Becker et al. (1977); and Francis, Korsch and Morris (1969) showed that both
patients' satisfaction and health beliefs were predictors of appointment keeping.
However, studies by Goldman et al. (1982) and Starkenburg, Rosner and Crowley (1988)
showed that satisfaction was not a significant predictor of appointment keeping.
Ware, Avery-Davies and Stewart reviewed the literature on patient satisfaction in
1978 and found 22 studies which analyzed satisfaction and health services utilization.
These 22 studies contained 30 comparisons of satisfaction and health care services, 26 of
which showed statistically significant positive relationships between satisfaction and
health services utilization. Furthermore, satisfaction scores have significantly predicted
one or more measures of volume of use of medical care services in studies reported by
Andersen (1968), Bice and White (1969), Hulka et al. (1971), Fabrega and Roberts
(1972), Brooks (1973), Wan and Soifer (1974), Kravits (1975) and Ware et al. (1975).
The relationship between satisfaction and patients' willingness to use particular
doctors, hospitals or health insurance plans has also been investigated. Marquis, Davies
and Ware (1983) found that dissatisfied patients were more likely to change physicians,
and Ware and Davies (1983) reported that dissatisfied patients were more likely to
disenroll from a health plan. Woodside, Frey and Daly (1989) found that patient
satisfaction was also related to patients' intentions to choose a particular hospital again.
The relationship between patients' satisfaction with a pharmacy and their
willingness to use that pharmacy is less clear. Although a number of researchers have
investigated the determinants of patients' satisfaction with their pharmacy, very few have
examined the consequences of satisfaction with the pharmacy. Most studies of pharmacy
patronage have suggested that the primary determinants of patronage are convenient
location and prompt service (Smith, 1992, p. 152), while other studies have shown that
satisfaction is also influenced by location and prompt service (Smith and Coons, 1993).
Although some authors have suggested that satisfaction mediates the relationship between
service attributes (e.g., locale and prompt service) and patronage, this relationship has
been hard to verify. Smith (1992) suggested that this may be due to the lack of variation
in "satisfaction with the pharmacy" responses. Most patients are satisfied or very
satisfied with their pharmacies which makes it difficult to find correlations between
satisfaction and patronage.
The lack of variability in satisfaction ratings may result from patients having low
expectations of their pharmacists. Several studies have found that patients do not expect
a "high-level" of professional service from their pharmacists (Mackowiak and Manasse,
1988; Schering Report XIV, 1992; Schommer, 1996; Spencer, 1974; Wiederholt and
Rosowski, 1996). In other words, if patients expect a "low-level" of service from
pharmacists, then low levels of performance may still yield satisfied consumers.
However, it should not be concluded that patients expect poor service. It may be that
patients' expectations of their pharmacists simply do not include those fimctions that
pharmacy experts would typically consider "high-level" service (e.g., pharmaceutical
care). As Jean Paul Gagnon suggested, "Some basic services done well is what the
customer would like to see." (1994, p. 93).
An important question regarding the evaluation of pharmaceutical care services in
community pharmacies is whether patients base their satisfaction ratings on the ability of
the pharmacist to help them manage their medications or disease. The pharmacy
literature does not provide a clear answer to this question. Fincham and Wertheimer
(1987) found that the primary predictors of satisfaction with HMO pharmacy services
5 ' ; ' t
were satisfaction with the HMO, convenience of prescription filHng, self-assessed
positive health status, an understanding of how to take the medication, and the view of
drugs as being inexpensive. This would suggest that satisfaction ratings are based, at
least in part, on the patient's health and mastery of their medication regimen. However,
this study did not determine whether the patients attributed their positive health status and
understanding of how to take the medication to the pharmacist. Therefore, the causal link
between satisfaction and health or medication use is not certain. Based upon a stream of
research on patients' expectations of their pharmacists, Schommer (1996) has concluded
that most patients do not expect to receive medication counseling from their pharmacists.
Hence, a lack of communication between pharmacist and patient is unlikely to have
deleterious effects on satisfaction. If satisfaction is not heavily dependent upon the
presence or absence of pharmacist-patient communication, then satisfaction scores are
unlikely to differentiate between basic medication counseling and pharmaceutical care.
Only one known study has attempted to confirm this (Nau and Lipowski, 1995).
The study by Nau and Lipowski (1995) found that asthma patients were generally
satisfied with their pharmacy despite low levels of interaction with the pharmacist.
Further analysis of these data suggest that patients who had any interaction with their
pharmacist were "very satisfied" whereas patients who had no interaction were
"indifferenf to "satisfied." Patients who received a higher level of interaction (e.g.,
pharmaceutical care) were no more satisfied than patients who received a lower level of
interaction. Although one could argue that a "ceiling-effect" exists in the measurement of
satisfaction with the pharmacy (i.e., that people have the same low expectations and that
any interaction with the pharmacist is sufficient to exceed those expectations), other
research suggests that patients have differing expectations (Mackowiak and Manasse,
1984; Schommer, 1996; Wiederholt and Rosowski, 1996). The studies by Mackowiak
and Manasse (1984) and by Schommer (1996) showed that patients' prior experience
with medication counseling was related to their current expectations for counseling.
However, the extent to which satisfaction with the pharmacy will change as a result of a
change in expectations is unknown.
Although numerous studies have examined patients' satisfaction with the
pharmacy, the ideal means for measuring satisfaction with the pharmacy has not been
determined. Most often, these measures have been developed in an ad hoc manner or
adapted from comparable organizations. Consequently, little may be known about the
reliability, validity, or sensitivity of the responses. The best knovra measure of
"satisfaction with the pharmacy" was developed by MacKeigan and Larson (1989).
These researchers adapted their measure of patient satisfaction with pharmacy services
from the Patient Satisfaction Questionnaire (PSQ) developed by Ware and colleagues
(1983). This pharmacy satisfaction instrument was developed using sound psychometric
technique and subjected to rigorous evaluation to establish its validity and reliability.
However, no studies have been published which establish the relationship between the
satisfaction scores derived from this instrument and patient behaviors.
It appears that satisfaction is related to persons utilization of health care services.
However, the relationship between satisfaction with the pharmacy and patients' use of
pharmacy services is less clear. As will be seen in the "synthesis of paradigms" section,
satisfaction may be closely related to other constructs used to explain patients' use of
health care services.
Perceived Quality and Value
Within the last decade, increasing attention has been paid to assessing and
improving the quality of health care in the United States. This has been driven by the
spread of managed care systems whose interest is in lowering the costs of care for their
enrollees. These organizations have based their actions on the premise that enhanced
service quality will lead to lower long-run expenditures. Simultaneously, consumers have
taken greater interest in the quality of care that they are receiving, thereby spurring on the
development of consumer report cards (McGee and Knutson, 1994).
The Institute of Medicine (lOM) has defined quality of care as "the degree to
which health care services for individuals and populations increase the likelihood of
desired health outcomes and are consistent with current professional guidelines" (Institute
of Medicine, 1990, p. 21). The Joint Commission for the Accreditation of Health Care
Organizations (JCAHO) has gone on to define quality in terms of nine performance
elements: efficacious, appropriate, available, timely, effective, continuous, safe, efficient,
respectful and caring (JCAHO, 1995, p. 90). While these definitions may be useful to
health care professionals, payors or accrediting organizations, it is likely that patients will
use more individualized definitions of quality in assessing health services.
Important quality-related issues for health behavior researchers are how patients
judge the quality of care, whether these judgments are consistent with expert ratings of
quality, how to measure these perceptions of quality and how patients' perceptions of
quality influence their behavior. It was traditionally assumed that patient satisfaction
ratings were reflective of the interpersonal quality of care, but perhaps not the technical
aspects of care (Linn and Greenfield, 1982). Further, health care providers doubted
whether patients satisfaction ratings reflected "objective" quality (i.e., experts ratings of
quality) (Locker and Dunt, 1 978; McMillan, 1 987).
Ware and colleagues, however, maintain that patients' ratings of health care
quality are valid. Findings presented by Davies and Ware (1988) and Kaplan and Ware
(1989) show that patients' ratings of quality agree with those of physicians. In these
studies, subjects viewed videotapes of physician-patient encounters in which the technical
and interpersonal aspects of care were manipulated. Physicians and patients rated the
encounters similarly on both the technical and interpersonal dimensions. The patient-
physician agreement did not vary by the patient's age or education level (i.e., young, well-
educated patients rated quality the same as older, less-educated patients). In another
study, Chang et al. (1984) videotaped six patient-provider encounters in which three
elements of care were deliberately manipulated (technical, psychosocial, £ind patient
participation) while courtesy was held constant. The subjects who rated the quality of
encounters successfully differentiated between high and low technical quality. The
aforementioned studies showed that consumers ratings of technical quality were not
influenced by the interpersonal aspects of care and that consumers' ratings of quality are
consistent with expert opinion. While this research shows that, in experimental
situations, patients can distinguish good from poor quality, the best way to measure
patients' perceptions of quality in "real world" situations is less clear.
vM' ''■ A'.Ji.
ii-i:* i i^i VI 'J 'i-
Although Ware and colleagues maintain that patients' perceptions of health care
quality are captured in satisfaction ratings, numerous services marketing researchers
suggest that perceived quality is conceptually distinct from satisfaction and thus should be
measured differently (Cronin and Taylor, 1992, 1994; Oliver, 1993; Taylor, 1994). The
general consensus of these authors is that service quality perceptions are long-term
consumer attitudes related to expectations, whereas patient satisfaction is a short-term,
encounter-specific consumer judgment.
Boulding, Kalra and Staelin (1997) found that these attitudes are difficult to
change if the patient has had a great deal of experience with the service provider. Their
research showed that prior expectations get "double-counted" as consumers update
perceptions of service quality. However, other authors (Rust, Inman and Zahorik, 1995)
found that consumers who have little or no experience with a service provider integrate
new quality information consistent with a Bayesian framework. Taken together, these
articles suggest that the best time to influence perceptions of quality is at the time when
consumers have little experience with the service.
Parasuraman, Zeithaml and Berry (1985) developed a measure of service quality
called SERVQUAL and refined the measure after extensive testing (Parasuraman, Berry
and Zeithaml, 1991). This measure is based upon a disconfirmation of expectations
paradigm along five dimensions of service quality: assurance, empathy, reliability,
responsiveness and tangibles). Hence, the instrument includes assessments of quality
expectations and perceived performance along each dimension. However, reviews of the
use of SERVQUAL have suggested that the inclusion of expectations in the measurement
of quality should be reconsidered (Babakus and Mangold, 1992; Cronin and Taylor, 1992;
Cronin and Taylor, 1 994; Teas, 1 992). Cronin and Taylor (1 992) attempted to improve
upon SERVQUAL by developing SERVPERF. This instrument eliminates the
measurement of quality expectations and measures only service performance. Taylor
(1994) suggests that health care practitioners use SERVPERF as the basis for measuring
health services quality since it has been shown to have a significant relationship with
behavioral intentions. The debate over performance-only (sometimes called perception-
only) versus performance-minus-expectations operationalizations continues, however
Zeithaml, Berry and Parasuraman offer the following guidance:
The perceptions-only operationalization is appropriate if the primary
purpose of measuring service quality is to attempt to explain the variance
in some dependent construct; the perceptions-minus-expectations
difference-score measure is appropriate if the primary purpose is to
diagnose accurately service shortfalls. (1996, p. 40)
Thus, when studying the relationship between quality and behavior, the most
appropriate operationalization of perceived quality is in terms of the consumer's
perception of provider performance. Several authors have found a relationship between
perceived quality and consumer behavioral intentions when using this framework.
Boulding et al. (1993) found a positive correlation between customers' perceptions of
service quality and a 2-item measure of repurchase intentions and willingness to
recommend. Zeithaml, Berry and Parasuraman (1996) investigated the link between
perceived quality and behavioral intentions across multiple service settings. Consistent
with their previously discussed recommendations regarding the operationalization of
perceived quality, they transformed their SERVQUAL difference scores into weighted-
average performance scores. They found relationships between the performance scores
and several types of behavioral intentions, particularly loyahy.
Several studies have investigated the link between perceived quality and
behavioral intentions in health care settings. Babakus and Mangold (1992) found that
perceived quality was related to patients' return intentions. Additionally, their work
suggests that the operationalization of perceived quality as a global performance measure
would be most appropriate for predicting behavior. Headley and Miller (1993) found that
perceived service quality, as measured by SERVQUAL, was related to clinic patients'
intent to complain, compliment, repeat purchase and switch providers. They also found
that scores on the service dimensions of reliability, dependability and empathy are the
best predictors of behavioral intentions. Nelson et al. (1992) used the Hospital Quality
Trends: Patient Judgment System (HQT: Patients) to evaluate quality at 51 hospitals. This
measure asked the patient to rate the performance of the service provider across 10
dimensions of care; however, upon conducting an exploratory factor analysis of their data
they concluded that the patients' ratings fell into four distinct dimensions:
medical/billing, nursing care/daily care, admissions, and discharge. They foimd that the
patients' evaluations of the medical/billing and discharge dimensions related to two of
three profitability indicators. Thus, the dimensions of perceived quality which occurred
near the end of the service encounter appeared to have a relationship with patients'
willingness to return.
As shown by the preceding discussion, patients' perceptions of health care quality
are consistent with expert ratings and predict their willingness to use health care services
in the future. However, some marketing researchers have suggested that the "perceived
value" of a product or service may be an even richer predictor of consumer behavior than
is perceived quality (Bolton and Drew, 1991; Dodds and Monroe, 1985; Holbrook and
Corfman, 1985). Holbrook and Corfman (1985) present a complex conceptualization of
value consisting of an interplay between three dimensions: extrinsic/intrinsic value, self-
oriented/other-oriented value, and active/passive value. These authors consider quality
within the context of this typology as extrinsic, self-oriented, passive value. This
research was important in that it suggested that quality is only one dimension in
consumers evaluation of goods; however, the authors provided little direction on how
consumers use this notion of value in making purchase decisions.
Dodds and Monroe (1985) provided a framework for the role of perceived value
in consumer decision-making. They suggested that consumers weigh the perceived
quality of a product against the price of the product to determine its value, and that the
perceived value of the product is associated with the intention to purchase the product.
Zeithaml (1988) used a qualitative approach to investigate consumers conceptualization
of value. She found that people think of value in four ways: 1) value is low price, 2)
value is whatever 1 want in a product, 3) value is the quality I get for the price I pay, 4)
value is what 1 get for what I give. This led her to define perceived value as "the
consumer's overall assessment of the utility of a product based on perceptions of what is
received and what is given" (1988, p. 14). This definition is consistent with Sawyer and
Dickson's (1984) conceptualization of value as a ratio of product attributes weighted by
their evaluations divided by product price weighted by its evaluation, and is similar to a
utility per dollar measure of value used by Hauser and colleagues (1981, 1983, 1986).
Wood and Scheer (1996) incorporate the work of Dodds and Monroe in their
conceptualization of perceived value as a tradeoff between the benefits the consumer
receives in the deal at hand and the costs the consumer incurs to obtain those benefits.
They also suggest that the definition of perceived costs should not only include expected
monetary outlays but also the consumer's assessment of the risk associated with the deal.
Wood and Scheer' s conceptualization was unique in that it explicitly incorporated
consumers' perceptions of the risk of purchasing a product into the formation of
perceived value. However, their test of the model did not provide a clear understanding
of the relationships among consumers' perceptions of benefits, cost and risk in purchase
Within healthcare, the weighing of benefits against costs and risks is not new.
Donabedian (1980) suggests that the degree of quality is a balance of benefits and risks.
He subsequently added the costs of care to this equation to form his unifying model of
quality care ~ benefits minus risks and costs. A few years later, Donabedian (1983)
discussed the relationship of quality and value in the following definitions of quality:
One requires that clients be active participants with the practitioner in
balancing the costs to themselves against the benefits to themselves, as
they value the costs and benefits. This is an essentially "individualized"
definition of quality. The other definition, which can be called "social,"
recognizes that society must, in the end, value all the costs and benefits,
including the costs and benefits to those other that the patient, and do so
with due regard to some principle of equity. (1983, p. 365)
'i '" .'
In these definitions, Donabedian appears to use the term "value" as the importance
one assigns to particular benefits or costs of care, whereas the term "quality" refers to the
relative importance of the benefits and costs. Nonetheless, he seems to suggest that
individuals and society must weigh the benefits against the costs (or risks) of care in
determining a course of action. This utilitarian approach is consistent with the perceived
value models described by Dodds and Monroe (1985), Wood and Scheer (1996) and
Although many researchers have studied patients' perceptions of the benefits or
costs of health care services (e.g., American Pharmaceutical Association, 1996; Becker
and Maiman, 1975; Reuben et al., 1994), very few have examined how patients'
perceptions of the value of health care services influence their utilization of those
services. Two notable exceptions are studies by Jones (1993) and Smith-Gooding (1995).
Jones (1993) tested the ability of a perceived value model to predict patients'
willingness to use a hospital again. This model was adapted from Zeithaml's (1988)
means-end model relating price quality and value. Jones found that perceived quality was
positively related to perceived value and that perceived value was positively related to
behavioral intentions; however, she also found that perceived sacrifice was positively
related to perceived value. In other words, people who perceived a greater sacrifice also
perceived a greater value. She suggested that this finding may be context-specific and
due to the influence of the perceived seriousness of the patient's illness and to her finding
of a positive relationship between perceived price and perceived quality. For example, in
situations where the patient is severely ill, the quality of the hospital may be very
important to the patient or his family. If they perceive a positive relationship between
their sacrifice and the quality of care being received, this would lead to a positive
relationship between sacrifice and value.
Smith-Gooding (1995) used a somewhat different perceived value model to
predict patients' choice between a small local hospital and a distant referral hospital. She
added importance weightings to the consumers' perceptions of hospital quality and
sacrifice. Overall, their choice of hospitals was positively associated with the perceived
quality and negatively associated with perceived sacrifice. Although Smith-Gooding did
not explicitly measure perceived value, she found that perceived sacrifice mediated the
relationship between perceived quality and hospital choice. She also found that for major
treatment situations, the patients assigned a great deal of importance to the quality ratings.
For minor treatment situations, the patients attached less importance to quality. Thus, in
situations where patients perceived that their health risk was minimal, the sacrifice
associated with obtaining care played a strong role in their choice of hospitals. When
there was a significant health risk, the perceived quality of the hospital was most
important in predicting hospital choice.
Both the Jones (1993) and Smith-Gooding (1995) articles point to the importance
of patients' perceived health risk as they value the quality (benefits) and costs of health
care services. Models which include perceptions of health risk along with perceptions of
the benefits and costs of using a health care service would seem to offer a greater ability
to predict patients' utilization of these services. The Health Belief Model (HBM)
includes these variables although not explicitly modeling their relationship in a perceived
value framework. The HBM will be discussed in greater detail in the following section.
• • Health Beliefs
Health services researchers have used a number of belief-based models to explain
patients' compliance with health-related behaviors and health services utilization. These
include Andersen's model of health services utilization (Andersen and Andersen, 1967;
Andersen and Newman, 1973; Aday and Andersen, 1974; Andersen, 1995), the Health
Belief Model (Rosenstock, 1966; Becker and Rosenstock, 1987), and models rooted in
Subjective Expected Utility (SEU) theory such as the Theory of Reasoned Action
(Fishbein and Ajzen, 1975) and the Theory of Planned Behavior (Ajzen, 1985).
Ronald Andersen, with the help of his mentor Odin Andersen, developed a model
for health service utilization which incorporated both individual and societal determinants
of behavior (Andersen and Andersen, 1967). The model suggests that predisposing
characteristics (demographics, social structure, health beliefs), enabling resources
(personal/family, community) and perceived need influence a person's utilization of
health services. Andersen viewed health beliefs as "attitudes, values, and knowledge that
people have about health and health services that might influence their subsequent
perceptions of need and use of health services" (1995, p. 2). Over the past twenty-nine
years, the model has gone through extensive revisions to encompass the impact of the
health care system and other external influences on health behaviors as well as to explain
the role of each component in shaping the outcomes of care.
=i- v.. "V
The purpose of this model was to "discover conditions that either faciUtate or
impede utiUzation" (Andersen, 1995, p. 4), thus it focuses on broad measures of access to
medical care. Although it is useful for understanding the influence of societal and
individual beliefs on one's perceived need for health care services, it does not provide an
explicit framework for patient decision making. The most popular explanation for the
role of health beliefs in shaping persons' health care decisions has been the Health Belief
The Health Belief Model (HBM) was first introduced by Rosenstock (1966). In
its initial form, the model held that four factors influenced patients' health care behaviors:
perceived susceptibility (the likelihood of developing a health problem), perceived
severity of the health problem, perceived benefits of obtaining care, and perceived
barriers to obtaining care. In subsequent years there have been several additions to the
model. These include "cues to action" (Janz and Becker, 1984), the value one places on
health (Lau et al., 1986), and health locus of control (Wallston and Wallston, 1981).
Additionally, the perceived barriers component has been remodeled to include Bandura's
(1977) concept of self-efficacy (Becker and Rosenstock, 1987).
The HBM has been used extensively in health behavior research. Harrison et al.
(1992) found over 100 articles using the HBM with adult subjects. Most of these studies
have supported the general framework of the HBM; however, there have been a myriad of
operational definitions used for each of the major components of the model (Conner and
Norman, 1994). The HBM and/or its components have been used to explain medication
compliance (Becker and Maiman, 1975), engagement in preventative health behaviors
(e.g., Carmel, Shani and Rosenberg, 1994), participation in health screenings (e.g., Aiken
et al., 1994; Blalock et al., 1990), and appointment keeping in clinics (e.g., Becker et al.,
1977; Starkenburg, Rosner and Crowley, 1988; Becker, Drachman and Kirscht, 1974).
Additionally, studies have shown that health beliefs are malleable and that promotions
designed to change one's health beliefs can influence health behaviors (e.g., Jones, Jones
and Katz, 1987; Klohn and Rogers, 1991).
Nonetheless, the HBM has its limitations. The model does not include clear
hypotheses about the relationships between its components nor their relative weights in
predicting health behaviors. Becker and Rosenstock (e.g., Rosenstock, 1966; Janz and
Becker, 1984; Becker and Maiman, 1975) have typically suggested that the susceptibility
and severity are combined to form the perceived health threat and that this perception
directly influences the likelihood of action. Simultaneously, they also suggest that the
individual weighs the benefits against the barriers in deciding whether to engage in the
health behavior. Other researchers have modeled the components in varying ways;
however, the majority of results indicate that the likelihood of engaging in a particular
behavior is increased when the perceived susceptibility, severity and benefits are high,
and when the perceived barriers or costs are low (van der Plight, 1994). The lack of
specificity in how these beliefs lead to behaviors has led some researchers to suggest that
the HBM be combined with subjective expected utility theory (Ronis and Harel, 1989;
Subjective expected utility theory provides an explicit mathematical framework
for the relationship of beliefs and behaviors (Edwards, 1954). Edwards' SEU theory
■ • / 30
assumes that people generally aim to maximize utility and prefer behavioral options that
are associated with the highest expected utility. The overall utility of a behavioral
alternative is based upon the summed products of the probability and utility of specific
outcomes or consequences. Thus,
where SEU^ is the subjective expected utility of behavioral alternative 7, P^ is the
perceived probability of outcome / of behavior^, and [7,^ is the subjective utility of
outcome / of behaviory. Each behavioral alternative will have a different SEU and
Edwards proposes that people will select the behavior with the highest SEU. This model
is conceptually similar to multi-attribute utility models (Edwards and Newmann, 1982)
and expectancy-value models (Carlson, 1956; Peak, 1955; Rosenberg, 1956). It has also
been suggested that Fishbein and Ajzen's models relating beliefs, attitudes and behaviors
(Fishbein 1967; Fishbein and Ajzen, 1975; Ajzen, 1985) are an extension of either the
SEU model (van der Plight, 1994) or the expectancy-value model (Eagly and Chaiken,
Ronis combined the Health Belief and Subjective Expected Utility Models to
study preventative health behaviors (Ronis and Harel, 1989; Ronis, 1992). In this
combined model, perceived susceptibility is considered to be the probability of an
outcome and perceived severity represents the (dis)utility associated with that outcome.
Thus, the susceptibility and severity should interact to represent the expected utility
(benefit) of engaging in a particular behavior. The utility (benefit) of engaging in a
preventative health behavior will typically be compared to inaction. The behavior with
the highest perceived utility (benefit) will be enacted. Ronis suggests that the costs or
barriers of each behavior are "quantified by a worsening in SEU associated with the
undesireable consequences of the actions (e.g., costing money, taking time, being
unpleasant)" (1992, p. 127). Thus, Ronis suggests that the costs of each behavior are
considered, along with the perceived benefits, in selecting the optimal behavior.
Ronis and Harel (1989) tested their combined model in a path-analytic study of
two preventative health behaviors (breast self-examination and obtaining professional
breast examination). The results supported all but two of the hypothesized relationships
among these variables. The two exceptions were: the effect of susceptibility on behavior
was not mediated by benefit, and susceptibility and severity did not interact.
Ronis (1992) used the same model to examine the dental flossing behavior of 662
adults. He measured the subjects' perceived susceptibility to gum disease conditional
upon behavior. In other words, they were asked to indicated their likelihood of
developing gum disease if they did not floss as well as their likelihood of developing gum
disease if they did floss. Perceived susceptibility to gum disease without flossing had a
direct effect on flossing behavior as well as an indirect effect through perceived benefits.
The perceived susceptibility to gum disease when flossing was negatively correlated with
the perceived benefits of flossing (i.e., the greater the perceived benefit of flossing, the
lower the perceived susceptibility to gum disease when flossing). The perceived severity
of gum disease had no significant correlation with perceived benefits or flossing behavior,
nor did it interact with perceived susceptibility. Ronis suggested that this was due to the
low reliability of the severity measure. The perceived costs of flossing also had a
significant negative correlation with flossing behavior.
Ronis' work is important for two reasons. First, he found that "conditional"
perceptions of susceptibility were related to the perceived benefits of the behavior and the
behavioral intentions. The failure to use questions about health threats that are
conditional on action may explain the previous inconsistent findings for these variables
(Becker et al., 1975; Becker et al., 1977; Janz and Becker, 1984; Langlie, 1977). Ronis'
finding is consistent with the recommendations of Fishbein and Ajzen (1975) regarding
the measurement of beliefs, attitudes and behaviors. They suggest that the strongest
relationships will be between measures that are compatible in action, target, context and
time. Thus, the congruency of Ronis' measures of susceptibility and behavior enhanced
his ability to find a relationship between the constructs.
The second important finding of Ronis was that perceived susceptibility to a
disease when not engaging in the preventative behavior is directly related to the intention
to engage in the preventative behavior. This suggests that when people are faced with
complex decisions, they may defer to simple decision rules (Payne, 1982). In regards to
flossing behavior, the thought process may resemble: "If 1 don't floss, I will get gum
disease; therefore, I should floss." However, this process seems contingent upon persons
valuing healthy gums and having minimal barriers to successfully engaging in the
behavior. Both studies by Ronis used situations in which people were likely to value the
outcome (e.g., no breast cancer, healthy gums) and were unlikely to encounter significant
barriers to the behavior (e.g., breast self-examination and dental flossing are inexpensive
■, i '<:'.• --, ■ ■ •. ,
and easy to perform). For behaviors with significant barriers (e.g., traveling to a health
center each month for a 30 minute meeting with a pharmacist), the perceived costs may
mediate the relationship between perceived susceptibility and the behavior.
Synthesis of Paradigms
As can be seen from the previous review, there have been a number of paradigms
used to explain patients' utilization of health care services. The overlap between these
paradigms has lead many authors to incorporate elements of one paradigm within another,
although there is not always agreement as to how these constructs relate. For example,
Bolton and Drew (1991) posited that satisfaction is an antecedent to perceived quality and
perceived value, whereas Oliver (1996) argues that perceived quality and value are
antecedents to satisfaction. Additionally, a number of authors have proposed various
relationships for health beliefs, attitudes towards a health behavior, and health behaviors
(Connor and Norman, 1994; Mullen et al., 1987; Oliver and Berger, 1979; Schwarzer,
1 992) although the conflicting results from these studies fail to provide overwhelming
support for any particular conceptualization.
Additionally, it is not clear which paradigm may be the best predictor of health
behaviors. Several studies have measured patients' satisfaction and health beliefs as
independent predictors of health care utilization. Several authors found that satisfaction
and health beliefs could predict compliance about equally (Becker, Drachman and Kirsch,
1974; Becker et al., 1977; Francis, Korsch and Morris, 1 969), while Starkenburg, Rosner
. i • < t -
and Crowley (1988) found that health beliefs were better predictors of follow-up visits to
a clinic than was satisfaction.
Others have compared the Health Belief Model with the Theory of Reasoned
Action and/or the Theory of Planned Behavior. Oliver and Berger (1979) compared the
extent to which a behavioral intentions model (based upon Fishbein and Ajzen's models)
and the Health Belief Model predicted subjects' obtaining swine flu shots. They found
that the behavioral intentions model explained over 50 percent of the behavioral intention
variance while the Health Belief Model explained only 35 percent of the behavioral
intention variance. However, both models predicted about 10 percent of the variance in
actual behavior. Mullen et al. (1987) found that the Theory of Reasoned Action and the
Health Belief Model performed similarly in predicting changes in smoking, exercise and
eating behaviors, and Connor and Norman (1994) found the Theory of Plarmed Behavior
and the Health Belief Model to have similar predictive ability regarding participation in
health screenings. In the Connor and Norman (1994) study, the Theory of Plarmed
Behavior, the Health Belief Model, and the combined models explained 52 percent, 55
percent and 61 percent of the variability in intention, respectively. However, the
combined models explained only 5 percent of actual health screening behavior. Oliver
and Berger (1979) and Connor and Norman (1994) both found that combining a
behavioral intentions model and Health Belief Model provided only a small increase in
predictive ability. This was likely due to the overlapping measurement of the same
constructs. Additionally, the authors suggest that the Health Belief Model provides
suboptimal prediction due to an unclear relationship between its elements and that the
measurement of cognitive elements in the Theory of Planned Behavior lacks sufficient
specificity to health related decision-making.
These shortcomings led Ronis and colleagues (Ronis and Harel, 1989; Ronis,
1992) to synthesize the Health Belief Model and Subjective Expected Utility theory in a
manner which provides explicit relationships between specfic health beliefs for health
related decision making. This model posits that persons weigh the benefits against the
costs of engaging in a health related behavior in determining a course of action and that
their perceived susceptibility of developing a health related problem when not engaging
in the behavior influences the perceived benefit of the behavior and engagment in the
behavior. Ronis suggests that when considering behavioral options, people will choose
the one that provides the highest expected utility (i.e., benefits versus costs and risks). As
discussed previously, this model accurately predicts dental flossing behavior (Ronis,
The "benefits versus costs" comparison of the Ronis model is similar to perceived
value models described by Dodds and Monroe (1985), Wood and Scheer (1996) and
Zeithaml (1988). Each of these authors suggest that when persons are deciding on a
course of action, they weigh "what they will get" against "what they must sacrifice" in
taking that course of action. In these models, the expected utility of the action is called
perceived value. Together, these models suggest that when persons are faced with the
decision of whether or not to utilize a preventative health service, they will weigh the
benefits and costs of using the service (wherein benefits may be conceptualized as a
reduction in health threat) to determine the value of that service to them. This perception
of value will influence their behavior (e.g., the greater the perceived value, the greater
probability of them using the health service).
The most common frameworks for explaining patients' use of health care services
are satisfaction, perceived quality and value, and health beliefs. The leading
conceptualization of satisfaction suggests that persons whose expectations are being met
or exceeded will continue to use that service. In most studies of patient satisfaction, it is
presumed that patients perceive a need for health care (i.e., they become sick), they
expect that a health care provider will or should improve their health in a compassionate
maimer, and that their decisions to continue use of that provider are based largely upon
the extent to which the service improved their health or was compassionate.
Although patients may leave a physician or health plan because their perceived
needs were not being met, they may also fail to utilize a particular health care service
because they do not perceive a need for that service (Andersen, 1995; Rosenstock, 1966).
If patients expect that their health will remain good without the health care service, they
may hold low expectations as to the ability of the service provider to improve their health.
In this case, it is possible that they would report positive satisfaction with the service
(i.e., their low expectations were met) but yet not perceive that they needed the service.
The cumulative evidence suggests that patients expect their pharmacist to provide
some basic information about medication use but do not expect their pharmacist to
provide pharmaceutical care services targeted at preventing problems with their disease.
■ ■-! ■■. //
• ',; ' ■ •
: , i,-H^- -^
■ .' ■■
If patients will be satisfied without participating in pharmaceutical care, then "satisfaction
with the pharmacy" ratings are unlikely to be an accurate predictor of patients' utilization
of the service. A specific rating of the patient's satisfaction with the pharmaceutical care
service may be more accurate, however this too may prove inadequate if patients do not
perceive a need for the service. Reports from pharmaceutical care implementation
projects at the Universities of Florida, Washington and Minnesota suggest that many
patients do not immediately perceive a need for pharmaceutical care.' Hence, until
patients become familiar with and begin to expect pharmaceutical care, satisfaction
ratings are unlikely to prove a useful predictor of pharmaceutical care service utilization.
Using the "perceived quality" of pharmaceutical care as a predictor of service
utilization may have similar limitations. If patients are unfamiliar with pharmaceutical
care, it may be difficult for them to differentiate between differing levels of quality.
Although research by Nau, Ried, and Lipowski (1997) suggests that patients perceive
providers of pharmaceutical care as more helpful than pharmacists who do not provide
pharmaceutical care, there is no evidence that patients' perceive non-providers of
pharmaceutical care as low quality practitioners or that these perceptions influence their
participation in pharmaceutical care. Additionally, quality perceptions are unlikely to
matter if the patients do not perceive the need for pharmaceutical care.
As shown in the previous section, the best model for explaining patients'
participation in care is likely to be one that encompasses patients' perceptions of the
' Much of this information was garnered through personal conversations with project
directors at each of these universities as well as through personal experience in the
University of Florida Therapeutic Outcomes Monitoring (TOM) project.
f-; *i' , - ■ •» ' '. . •
; : ■: .-' ■: ■ • ^ 38
potential benefits and costs of pharmaceutical care. The perceived benefits may best be
conceptualized as the belief that the use of the health service can lead to a reduction in
health threat. The difference between the perceived benefits and costs can be termed
"perceived value" or "expected utility". It is the perceived value of the service that
should be most closely related to the patient's utilization of pharmaceutical care. A
model of the perceived value of pharmaceutical care and its relationship to patient
behavior is described in Chapter 3.
RATIONALE AND THEORETICAL FRAMEWORK
As discussed in the previous chapter, a number of theoretical frameworks
have been used to explain patients' use of health services. There is considerable overlap
among these frameworks and several authors have advocated combining some of them
(Connor and Norman, 1994; Oliver and Berger, 1979; Ronis, 1992). The combination
which underlies the theoretical framework for this study was first introduced by Ronis
and colleagues (Ronis and Harel, 1989; Ronis, 1992). They combined the Health Belief
Model (HBM) and Subjective Expected Utility (SEU) theory in two studies of health-
The Ronis model suggests that persons decide whether to engage in a particular
health behavior by weighing the benefits of the behavior against the costs of engaging in
the behavior. The ratio of benefits to costs is the subjective expected utility (SEU) of the
behavior. The SEU of the target behavior is weighed against the SEU of other behaviors
(which may include 'doing nothing'). The behavior with the highest SEU will be
selected. The model also suggests that the perceived benefits of engaging in a preventive
health behavior are influenced by an individual's evaluation of his or her susceptibility to
the corresponding health threat and the severity of that health threat. The multiplicative
combination of susceptibility and severity has been called "perceived risk" (van der
Plight, 1994) and "perceived threat" (Janz and Becker, 1984). Hence, the perceived
benefit of the behavior may be thought of as the extent to which people feel that they will
experience a reduction in their susceptibility to a health threat and/or a minimization of
the severity of the health threat.
The following example may clarify these relationships. A person with asthma
may be offered the opportunity to participate in an asthma monitoring service. In deciding
whether to participate in the asthma monitoring service, the person would weigh the
potential benefit of the service against the cost of the service. His perception of the
benefit of participating in the asthma monitoring service would be shaped by his
evaluation of the service provider's ability to help him reduce the "threaf ' of breathing
problems. The perceived costs of participation may include monetary and nonmonetary
(e.g., time, stress) costs. If the benefit/cost ratio for participating in the asthma
monitoring service is more desirable than the benefit/cost ratio for not participating in the
service, he should choose to participate.
While Ronis suggests that the "benefit/cost ratio" is the subjective expected utility
of the behavioral option, he does not explicitly include expected utility in his model.
However, the weighing of benefits and costs is consistent with perceived value models
which do explicitly depict this construct (Dodds and Monroe, 1985; Zeithaml, 1988).
These models define perceived value as the net utility which results from weighing what
one expects to get from the service (i.e., perceived benefits) against what one expects to
give in receiving the service (i.e., perceived costs). The theoretical framework for this
study will use the term "perceived value" to represent the expected utility of participating
in the pharmaceutical care service.
An important finding in Ronis' test of his model was that "conditional" measures
of susceptibility and severity provided better prediction of perceived benefits and
behavior than did "unconditional" measures. The measures were considered
"conditional" if the perception of susceptibility or severity was dependent on adherence to
the behavior. Ronis (1992) used the following questions to measure one's perceived
susceptibility to gum disease conditional on flossing. Perceived susceptibility with
flossing was stated, "If you brush and floss your teeth daily, how likely do you think it is
that you will develop gum disease during the next year?" Perceived susceptibility
without flossing was stated, "If you brush your teeth daily, but do not floss, how likely do
you think it is that you will develop gum disease within the next year?" The
unconditional measure of susceptibility stated, "How likely do you think it is that you will
develop gum disease during the next year?" Ronis' findings on this issue are consistent
with van der Plight's (1994) recommendation that measures of susceptibility and severity
be made conditional on action. Consequently, questions pertaining to perceived health
threats in this study will be made conditional on participafion in the pharmaceutical care
Ronis (1992) tested not only the independent influence of conditional
susceptibility and severity perceptions on perceived benefits, but also the interactive
influence of these variables on perceived benefits. He found no interaction and suggested
that this may be due to the low reliability of the severity measure. 1 believe this occurred
/ f . .'
> *> . ■ ^
due to his selection of two health conditions for which people are likely to hold very
similar perceptions of severity. Breast cancer is likely to be perceived as severe by nearly
all women and gingivitis is likely to be considered non-severe by most persons. For
diseases like asthma, where symptoms can vary greatly in frequency and severity, there is
likely to be greater variability amongst persons' perceptions of the severity of their
breathing problems. Hence, a lack of variability in persons' perceptions of the severity of
particular health problems may obfuscate the role of perceived severity in patients'
decisions to engage in preventive health behaviors.
Regardless of the variability of these two perceptions, it may also be true that
persons do not form truly independent perceptions of susceptibility and severity when
evaluating the "threat" of a particular health problem. Recent versions of health behavior
models (Janz and Becker, 1984; Schwarzer, 1992) and models of "perceived risk" (van
der Plight, 1994) suggest that perceptions of susceptibility and severity combine to form a
global perception of the "health threat." Consequently, the proposed model contains
conditional health threat variables which encompass conditional perceptions of both
susceptibility and severity for a particular health threat. However, there may be
considerable variability in the extent to which the perceived severity of a specific health
problem influences the more globally perceived "health threat" associated with that
problem. Consequently, the operational definitions for perceived "health threat" should
vary according to the nature of the threat.
The nature of the threat can take many forms. Since asthma often has noticeable
effects on one's daily activities, people may think of the threat in terms of its impact on
their ability to work, sleep, play or socialize. However, for persons taking anti-coagulant
medications, the perceived threat may be the long-term chance of experiencing a stroke or
having bleeding complications (i.e., things that are rare but very serious) rather than a
readily noticeable impairment of daily activities.
The theoretical framework is depicted in Figure 3-1. Definitions of the variables
represented in this framework are as follows:
Behavioral intention is the subject's intention to regularly participate in the
service. . .
Perceived value is the subject's overall evaluation of the benefits versus costs of
participation in the pharmaceutical care service.
Perceived benefits are what the subject perceives that he or she will
derive from participation in the pharmaceutical care service.
Perceived costs are what the subject perceives that he or she will have to
sacrifice to participate in the pharmaceutical care serivce.
Perceived threat ~ No participation is the subject's evaluation of his or
her susceptiblity to a particular health threat and the severity of that threat
if the subject does not participate in the pharmaceutical care service.
Perceived threat ~ Participation is the subject's evaluation of his or her
susceptibility to a particular health threat and the severity of that threat if
the subject participates in the pharmaceutical care service.
Two global hypotheses about the goodness of fit of the perceived value model are
posited, as are five specific hypotheses regarding associations between model
Global Hypotheses ' .
H,: The perceived value model will demonstrate adequate fit with the data for
predicting patients' intentions to participate in pharmaceutical care.
Hj: The removal of the conditional threat variables from the perceived value
model will not improve the goodness of fit of the model.
Hypotheses for Model Components
H3: The perceived value of the pharmaceutical care service will have a direct,
positive effect on the subjects' intentions to participate regularly in the service.
H4: The perceived benefits of the pharmaceutical care service will have a direct,
positive effect on the perceived value of the pharmaceutical care service.
H5: The perceived costs of the pharmaceutical care service will have a direct,
negative effect on the perceived value of the pharmaceutical care service.
HgC The perceived threat-no participation will have a direct, positive effect on the
perceived benefits of the pharmaceutical care service.
H7: The perceived threat— participation will have a direct, negative effect on the
perceived benefits of the pharmaceutical care service.
0"'( i "y ■-',>- i ■ ■ ., '■": ;,: : ^ It M
This section delineates the methods and procedures to used in meeting the
research objectives. It encompasses sample selection, data collection, variable
definitions, instrument development and validation, data analysis and limitations.
The subjects for this study were persons enrolled in an anticoagulation (AC) clinic
at the Veterans Administration (VA) hospital in Gainesville, Florida. The AC clinic is
staffed by a pharmacist coordinator, a pharmacy resident, a pharmacy student and a clerk.
The pharmacists assist the patients in maintaining an adequate level of anti-coagulation
and identify, resolve and prevent drug-related problems. The pharmacists do this by
educating the patient on the use of warfarin (e.g., when to take the drug, what foods to
avoid, signs and symptoms of common drug-related problems) and by meeting with the
patients on a regular basis to monitor their blood levels of warfarin and to assess any
symptoms they may be related to the use of warfarin. The frequency of the visits is
determined by the pharmacist and depends upon the patient's clinical condition and
stability of the warfarin levels. Patients whose clinical condition and warfarin levels are
stable will typically meet with the pharmacist every six to eight weeks.
All persons who had visited the AC clinic at least two times were eligible for
inclusion in this study. The reason for requiring at least two visits was to ensure that the
subjects had some experience with pharmaceutical care prior to answering questions
regarding the AC clinic services.
Data Collection Procedures
This research employed a non-experimental, cross-sectional design. Data were
collected over a five week period in January and February 1997. Patients who visited the
AC clinic were asked to complete a written survey. They were informed that it was
optional and confidential. If the patient was unable to complete the survey on his own,
the investigator read the questions and response options to the patient and recorded the
patient's response. Patients who were scheduled to visit the AC clinic during the study
period, but who failed to keep their appointment, were contacted by telephone. Four
attempts to contact these patients by telephone were made before declaring a non-
response. J H ' * f -"'•■'0' i
In path analysis, a causal model is specified as a system of linear equations.
Many of the variables in the causal model will serve as an independent variable in one
equation and a dependent variable in another equation. Thus, rather than describing the
variables as solely independent or dependent, it makes more sense to refer to them as
exogenous or endogenous variables. Exogenous variables have values that are
determined outside the system (e.g., age, gender). Endogenous variables have values that
are determined jointly by the system of equations. The variable definitions are presented
in the following sections. The final version of the research instrument is presented in
The following exogenous variables were measured: age, gender and ethnicity.
These variables were included in the survey because previous research has found them to
be associated with health beliefs (Becker, 1974; Brown, 1994), however they were
ultimately excluded from the path analysis due to their lack of sufficient variability.
Perceived threat-No participation '
This variable reflects the degree to which an individual feels threatened by
pertinent health problems when he does not participate in the pharmaceutical care service.
It focuses on the subject's perception of his likelihood of experiencing bleeding problems
and/or clot formation conditional upon not meeting with the provider on a regular basis.
Each of these perceptions are measured on a five-point scale fi-om 1 "very low" to 5 "very
high" and are found in the questionnaire as items 16 and 18. The score on the two
questions are summed to obtain the scale score.
■I* ■ *
' In all model depictions, the conditional threat variables bear different variable names.
Perceived threat—No participation is named "NoCare" and Perceived threat— Participation
is named "Care." This was done because the software used for data analysis does not
permit variable names greater than eight characters
Perceived threat— Participation
This variable reflects the degree to which an individual feels threatened by
pertinent health problems when he participates in the pharmaceutical care service. It
focuses on the subject's perception of his likelihood of experiencing bleeding problems
and/or clot formation conditional upon his meeting regularly with the clinic provider.
Each of these perceptions are measured on a five-point scale from 1 "very low" to 5 "very
high" and are found in the questionnaire as items 17 and 19. The score on the two
questions are summed to obtain the scale score.
This variable reflects the degree to which an individual perceives that he/she has
benefited from the pharmaceutical care service. The benefits were operationally defined
as both a reduction in health threat and as service component benefits. The perceived
benefits variable defined as the reduction in health threat (questionnaire items 13 and 14)
was comprised of two statements: 1) Meeting with the clinic provider on a regular basis
decreases my chances of forming a clot in my blood; and 2) Meeting with the clinic
provider on a regular basis decreases my chance of having problems with my warfarin.
The subjects indicated their agreement using a five-point Likert-type scale anchored by 1
"Strongly Disagree" and 5 "Strongly Agree" wherein 5 represented higher perceived
benefits. The responses to these questions were summed to obtain the scale score.
- I:. ._. ... '-^ .
The perceived benefits variable defined as service component benefits asked the
subjects to indicate the benefit of five components of the pharmaceutical care service.
These components were 1) explaining how to take warfarin; 2) explaining what foods to
avoid when taking warfarin; 3) monitoring your blood levels of warfarin; 4) discussing
whether you have had problems with bleeding; and 5) discussing whether you have had
problems with bruising. The response categories for these questions were: 1-not
beneficial; 2-somewhat beneficial; 3-fairly beneficial; and 4-very beneficial. The
responses to these questions were summed to obtain the scale score.
This variable reflects the perceived non-monetary costs of participating in the
pharmaceutical care service. The non-monetary costs most likely to be associated with
these services are time costs and emotional costs. Time costs (questionnaire items 8, 9
and 10) may be incurred because of inconvenient meeting times, meetings that last too
long or meetings that are too frequent. Emotional costs (questionnaire items 1 1 and 12)
may result from discomfort or stress. The perceived costs are measured on a five-point
Likert-type scale anchored by 1 "Strongly Disagree" and 5 "Strongly Agree" wherein 5
represents higher perceived costs. The responses to these five questions were summed to
obtain the scale score.
Perceived Value '*-
This variable reflects the extent to which the respondent believes that use of the
pharmaceutical care service is worth the time it takes. The subject is asked to indicate his
agreement with three statements: 1) Taking with the provider in the clinic about how to
take warfarin is worth the time it takes; 2) Talking with the clinic provider about my
blood levels of warfarin is worth the time it takes; and 3) Meeting with the clinic provider
on a regular basis is worth the time it takes. These appear in the questionnaire as items 5,
■■ . , <l%
6 and 7. The agreement is measured on a five-point Likert-type scale anchored by 1
"Strongly Disagree" and 5 "Strongly Agree" wherein 5 represents greater perceived value.
The score from each of the three statements are summed to obtain the scale score.
This variable reflects the extent to which the individual desires to interact with the
clinic pharmacist. The subjects are asked to indicate if they would prefer to not return to
the clinic anymore, meet with the provider only when they have a question or concern, or
to continue meeting with the provider on a regular basis. Because patients must visit the
clinic to obtain refills of warfarin, they may intend to visit the clinic to obtain the warfarin
regardless of their opinions about the clinic services. To separate the subjects' intentions
to obtain medication from their intentions to obtain clinic services, the statement was
worded as follows: "If I could get my warfarin prescription without coming to this clinic,
I would prefer to . . ." By asking what the respondent would "prefer" to do, the item
strays somewhat from Fishbein and Ajzen's (1975) conceptualization of behavioral intent
as "people's expectancies about their own behavior in a given setting" (p. 288).
However, research on behavioral intentions has found that the nature, and existence, of
intentions varies between persons and situations (see Eagly and Chaiken, 1993 for a
review of this literature). This led Sternberg (1990) to suggest that intention be
conceptualized as a continuum running from vaguely formulated thoughts about future
behavior to clear-cut plans that one is going to engage in a particular behavior at a
particular point in time. If the lay definition of "preference" is what one would do if there
were no constraints on his or her behavior, then preferences and intentions should be
similar in situations assuming no behavioral constraints. Since the goal of the item was
to measure the subject's intention to use the service without the existing constraint related
to prescription refills, the item wording should be appropriate.
Instrument Development and Validation
The study instrument was based upon interviews with patients who have
experienced pharmaceutical care as well as discussions with providers in the anti-
coagulation clinic. The experienced pharmaceutical care users were persons enrolled in
AvMed health plan who had participated in Therapeutic Outcomes Monitoring (TOM)
services provided by their pharmacist. Fifteen asthma patients and/or their parents were
interviewed by telephone or completed a mail questionnaire. They were asked open
ended questions about the benefits they derived from the TOM services as well as their
perceptions of the non-monetary costs and value of TOM services. These interviews
suggested that persons perceive the most valuable component of pharmaceutical care to
be the pharmacist's instructions on how to use the medications, followed by the disease-
related monitoring by the pharmacist. Hence, the perceived benefits variable
operationally defined by its service components contained items that related to
medication-related information and monitoring.
Interviews with two patients taking anticoagulant medication as well as
discussions with the pharmacist-coordinator of an anticoagulation clinic suggested that
the health-related concerns associated with taking anticoagulant medication were forming
. :■;.,.. 53
a blood clot (resulting from too little medication) and excessive bleeding or bruising
(resulting from too much medication). Hence, the conditional health threat items focused
on these concerns.
Validation of Instrument
Nunnally suggests that "content validity rests mainly on appeals to reason
regarding the adequacy with which important content has been sampled and on the
adequacy with which the content has been cast in the form of test items" (1978, p. 93).
The content validity of the instrument used in this study was assessed via expert review
and pilot-testing. Experts in health services research from the Department of Pharmacy
Health Care Administration reviewed the instrument to determine the relevance of the
questions to the conceptual domains and existing theory. The instrument was also
reviewed by the pharmacist-coordinator of the anticoagulation clinic at the Gainesville
Veteran's Administration (VA) Hospital. Based upon the expert feedback, minor
changes were made in question wording and ordering.
Following the expert review, a pilot test was conducted with 10 anticoagulation
patients. The subjects completed the survey in the anticoagulation clinic while waiting for
their clinic visit. A short debriefing was conducted to determine if the patients
interpreted the questions as intended and whether the concerns addressed by these
questions were relevant to the patients' willingness to talk with a pharmacist. The
subjects felt the language used was understandable and their interpretation of the meaning
of the questions was consistent with the intended meaning. Additionally, all of the
subjects agreed that the most relevant heahh concerns when taking anti-coagulant
medications were blood clots and excessive bleeding or bruising. Two subjects stated
that they could not assess the likelihood of developing a blood clot or bleeding problems,
however the other eight subjects stated that they did perceive that they were less likely to
develop problems when visiting the clinic on a regular basis. Based upon this feedback,
it was decided that the items would be used as currently worded. The final instrument is
shown in Appendix A.
A factor analysis was conducted to determine whether the item responses
"clustered" together consistent with the operational definitions of each construct. The
items comprising the following variables were included: value, benefits (threat reduction
operationalization), cost, perceived threat—no care, perceived threat— care. Factors were
extracted using principal-components analysis and were subjected to an orthogonal
The correlations of items within and between subscales were also examined.
Ideally, the correlations among items within a subscale should be higher than the
correlations of items between subscales (Nunnally, 1978).
Reliability is a necessary but not sufficient condition for validity (Crocker and
Algina, 1986). While there are numerous types of reliability, internal consistency is
particularly important for multi-item scales. Internal consistency can be evaluated by
calculating coefficient alpha and item-to-total correlations. Coefficient alpha provides an
estimate of how consistent subjects performed across items measuring the same construct
(Crocker and Algina, 1986). An alpha of greater than 0.60 is generally considered
acceptable (Nunnally, 1978). Corrected item to total correlations are the correlation of
item scores to the total score of the remaining items in the scale. Corrected item to total
correlations are especially relevant when there are few items in a scale (Ferketich, 1991),
and Nmmally (1978) suggests that corrected correlations above 0.30 may be sufficient.
The revised coefficient alpha indicates the resulting alpha if an item is deleted from the
scale. If there is a substantial improvement in alpha when the item is dropped, then it
may be prudent to delete the item. However, decisions regarding the deletion of the item
should be based upon conceptual as well as statistical considerations. Coefficient alpha
was calculated for each scale along with corrected item to total correlations and revised
coefficient alphas. These are presented in Table 5-2 in the following chapter.
Path-analyses of the theoretical model and three alternatives were conducted using
Amos software version 3.6 (Small Waters Corporation, 1996). The squared multiple-
correlation coefficient for each endogenous variable was calculated along with
unstandardized and standardized regression weights for each hypothesized relationship.
Bollen and Long (1973) also suggest that several goodness-of-fit indices be reported
when analyzing how well the data fit a theoretical model, and Tanaka (1993) suggests
that these indices be selected to give a multifaceted evaluation of model fit. Amos reports
nearly 30 different goodness-of-fit indices for each model. To simplify the interpretation
of the results, the following indices were selected to evaluate model fit: chi-square and
degrees of freedom, Tucker-Lewis Index (TLI) and Akaike Information Criterion (AIC).
Chi-square is sample-size dependent and was selected because of its familiarity to
researchers. The TLI (Bentler and Bonnett, 1980; Tucker and Lewis, 1973) was selected
because it is sample-size independent, its normed scale is easy to interpret, and it is
relatively unaffected by model complexity. The AIC (Akaike, 1987) is adversely affected
by increasing model complexity and is ideal for model comparison (Joreskog, 1993).
The ideal fit between the data and theoretical model would be evidenced by a ratio
of chi-square to degrees of freedom below 3:1 (Carmines and Mclver, 1981, p. 80); by a
TLI above 0.9 (Bentler and Bonnett, 1980, p. 600); and by an AIC that is low relative to
alternative models (Joreskog, 1993, p. 307). Hence, when comparing models, the best fit
would be the model with the lowest ratio of chi-square to degrees of freedom, the highest
TLI or the lowest AIC. An additional means of comparing models is by their chi-square
difference. This statistic is merely the difference in chi-square and degrees of fi-eedom
between the two models. A non-significant chi-square difference suggests that the
models fit the data equally as well. -f ';!^^
To test the first global hypothesis regarding the fit of the data to the theoretical
model, the chi-square/degrees of freedom, TLI and AIC were calculated for the model
depicted in Figure 4-1. The hypothesis will be confirmed (i.e., model deemed acceptable)
by a ratio of chi-square to degrees of fi-eedom below 3:1 and a TLI above 0.9.
This model was first tested with the perceived benefits variable being
operationally defined as "perceived threat reduction," then with the perceived benefits
variable being operationally defined as "service components," then with both
operationalizations of perceived benefits. Since the "perceived threat reduction"
operationalization provided the best model fit, fiirther model testing was conducted using
only this operational definition of perceived benefits. The rejected models are shown in
Discussions with the subjects regarding the clinic services suggested that their
perceptions of the benefits of the service may be influencing their perceptions of the costs
of using the serivce. The zero-order correlations between perceived benefits and
perceived costs were consistent with this finding. Consequently, the model was revised
to include the influence of perceived benefits on perceived costs (Figure 4-2). This new
model was compared to the originally proposed model for goodness-of-fit with the data.
Because the "revised" model exhibited superior fit, it served as the basis for fiirther
To test the second global hypothesis, which posited "the removal of the
condifional threat variables will not improve the goodness-of-fit of the theoretical
model," the chi -square/degrees of freedom, TLI and AIC were calculated for the model
represented in Figure 4-3. In this model, the paths from the conditional threat variables to
perceived benefits were constrained to zero. This essentially removes the influence of the
conditional threat variables while working within the same saturated model as Figure 4-2.
The goodness-of-fit indices for the model in Figure 4-3 were compared to the "revised"
model in Figure 4-2. Hypothesis 2 will be accepted if the more parsimonious model does
not exhibit a lower ratio of chi-square to degrees of freedom, a higher TLI, lower AIC or
significant chi-square difference.
Since the factor analysis suggested that the perceived cost variable may be
conceptualized as two separate constructs (time costs and emotional costs), the model
was further revised to represent perceived costs as two distinct variables (Figure 4-4).
The goodness-of-fit indices for the model in Figure 4-4 were compared to the indices for
the model in Figure 4-2. *.
\ W /
\ ^ /
\ W /
To test the five specific hypotheses regarding associations among the endogenous
variables, the standardized regression coefficients calculated by AMOS were examined.
The model in Figure 4-2 was the basis for this analysis. Hypotheses were supported if the
association was in the predicted direction and if the regression coefficient (beta) was
statistically significant (p < 0.05) when controlling for all other endogenous variables.
Since this study is the first to explicitly examine patients' perceptions of the
benefits, costs and value of pharmaceutical care, there will be few benchmarks against
which to compare these results. Although recent studies of consumer interest in
pharmaceutical care suggest that people are receptive to the idea of having a pharmacist
more involved in managing their drug therapy (American Pharmaceutical Association,
1996), no one has systematically examined the perceptions of patients who have
experienced pharmaceutical care.
While this study tested the ability of the perceived value model to explain
patients' behavioral intentions, it did not measure actual behavior. Measuring behavior
prospectively would require a time frame that is too lengthy for this dissertation.
However, behavioral intentions have been shown to be related to actual behavior in
several studies (Connor and Norman, 1994; Oliver and Berger, 1979). Thus, there is
reason to believe that the subjects would generally behave as they indicate on the
behavioral intention measure, particularly when there are few constraints on their
The generalizability of these findings is Hmited to the sample used in the study.
The subjects were all veterans and were primarily older, Caucasion men. While there is
no reason to suspect that the conceptual relationships among the variables would differ
with a more heterogenous sample, it is possible that the veterans are less, or perhaps
more, concerned than the general population about particular health threats or the time
required for clinic visits. Hence, their perception of the value of anticoagulant-focused
pharmaceutical care may be different than other persons' perceptions of similar
pharmaceutical care services.
The items used to measure each perception are probably not perfect
representations of the constructs. While a factor analysis was conducted to provide
insight on the relationships among these items, the factor analysis carmot determine the
causal nature of the relationships. Consequently, items may be strongly associated (and
appear in the same factor) because one strongly influences the other or because they
represent the same construct. For example, items from the benefits and value variables
. V f \ ■■
may appear in the same factor because of the strong influence of perceived benefits on
perceived value, or because they are not conceptually distinct. Because of the cross-
sectional design of this study, it will not be possible to determine whether people form
their perceptions of benefits prior to their perceptions of value.
By collecting data during the clinic visits, the subjects may have felt predisposed
to be less critical of the clinic providers. Although subjects were informed that their
individual responses would not be shared with the clinic provider, they may have still felt
obligated to provide socially desirable feedback on the clinic services.
One hundred fifty-four subjects completed the survey, representing 79% of the
194 patients who had scheduled clinic appointments during the six-week data collection
period. One hundred twenty-four of the 1 54 respondents completed a written survey
with no help, while 24 subjects in the clinic required help reading the survey. Another six
subjects were surveyed by telephone due to their failure to keep a scheduled clinic
appointment. The 40 non-respondents either refiised the survey or were unable to be
reached by telephone. :
The mean age of the respondents was 66 years and 1 52 (98.7%) were male (Table
5-1). One hundred thirty-nine (90.3%) respondents were Caucasian. Seventeen (1 1%)
subjects reported an emergency center visit and 20 (13%) reported a hospitalization
within the past year related to blood clots or bleeding problems. Seventy-six percent of
the subjects reported taking warfarin for greater than one year. One hundred twenty-
seven (82.5%) subjects reported talking with their physician about warfarin during the
past year, however because some patients mistake the clinic pharmacist for a physician, it
was unclear how many subjects truly talked with their physician regarding warfarin.
Sample Description (N = 1 54)
2 ( 1.3)
10 ( 6.5)
2 ( 1.3)
3 ( 1.9)
ER visit within past year
for bleeding or blood clots
Hospitalized within past year
for bleeding or blod clots
MD visit within past year
Duration of warfarin therapy:
12 ( 7.8)
Reported as Mean ± SD
Perceived Threat— No Participation
This subscale was comprised of two items regarding the subjects' perception of
the likelihood of their developing blood clots or bleeding problems if they did not meet
with the clinic provider on a regular basis. The subscale range was 2-10 with a mean and
standard deviation of 7.0 and 1.9, respectively (Table 5-2). The zero-order correlation for
the two items was 0.65 . ' . . '^
1- ■ t
Perceived Threat— Participation ^ •
This subscale was comprised of two items regarding the subjects' perception of
the likelihood of their developing blood clots or bleeding problems if they meet with the
clinic provider on a regular basis. The subscale range was 2-10 with a mean and standard
deviation of 4.0 and 1.5, respectively (Table 5-2). The zero-order correlation for the two
items was 0.44.
The perceived benefits were operationally defined as both service component
benefits and perceived threat reduction. The service component operationalization
consisted of five items each of which was measured on a 4-point response scale. The
subscale range was 4-20 with a mean and standard deviation of 16.9 and 3.6, respectively
(Table 5-2). Cronbach's alpha for these five items was 0.91. The item-to-total
correlations and Cronbach's alpha when each item was removed suggest that the subscale
has adequate internal consistency (Appendix C). The mean is above the midpoint of the
subscale suggesting the clinic services were generally perceived as beneficial.
Variables and Items
r ?'/v }'^ fi '■
..f '.- ■ .. .
., . ■
* For all subscales, higher scores represent greater amounts of the construct,
t For subscales with only two items, the zero-order correlation between the
items is reported.
The perceived threat reduction operationalization consisted of two items regarding
the subjects' perceptions of whether the regular clinic visits decrease the likelihood of
their experiencing blood clots or problems with the warfarin. The subscale range was 2-
10 with a mean and standard deviation of 7.9 and 2.0, respectively (Table 5-2). The zero-
order correlation for the two items was 0.84. The mean was above the subscale midpoint,
suggesting that the clinic services were generally perceived as being beneficial via threat
The perceived costs subscale was comprised of five items covering two domains:
time costs and emotional costs. The subscale range was 5-25 with a mean and standard
deviation of 12.0 and 3.9, respectively (Table 5-2). Cronbach's alpha for the five items
was 0.79. The item-to-total correlations and Cronbach's alpha when each item was
removed suggest that the subscale has adequate internal consistency (Appendix C). The
mean is slightly below the scale midpoint suggesting that the overall costs of attending
the clinic were generally perceived to be moderate.
The factor analysis suggested that the perceived cost variable could be
conceptualized as two distinct constructs (emotional costs and time costs). Hence, the
two items relating to stress and discomfort were summed to obtain an emotional cost
score and the three items relating to time were summed to obtain a time cost score. The
emotional cost subscale range was 2-10 with a mean and standard deviation of 3.9 and
1 .5, respectively. The correlation between the two items was 0.55. The time cost
subscale range was 3-15 with a mean and standard deviation of 8.1 and 2.9, respectively.
Cronbach's alpha for the three items was 0.79.
The perceived value subscale was comprised of three items each of which was
measured on a five-point agreement scale. The subscale range was 3-15 with a mean and
standard deviation of 12.2 and 3.1, respectively (Table 5-2). Cronbach's alpha for the
three items was 0.92. The item-to-total correlations and Cronbach's alpha when each
item was removed suggest that the subscale has adequate internal consistency (Appendix
C). The mean is above the midpoint of the subscale suggesting that the clinic services
were generally perceived as worthwhile.
The distribution of responses to the behavioral intention question was: a) not
meet with the clinic provider anymore, N=9 (5.8%); b) meet with the clinic provider only
when I have a question about my health or medication, N = 43 (27.9%); c) continue to
meet with the clinic provider on a regular basis, N = 1 02 (66.2%).
' ■ '< ■ Miscellaneous Questions
Two items required the subjects to indicate their agreement with statements
regarding the seriousness of developing blood clots or bleeding complications from
warfarin. The responses were scored on a five-point agreement scale with 5 representing
"strongly agree." For the item that stated "Developing a blood clot is a very serious health
problem," the mean and standard deviation were 4.9 and 0.4, respectively. For the item
that stated "Developing bleeding complications from warfarin is a very serious health
problem," the mean and standard deviation were 4.4 and 0.9, respectively. These scores
suggest that most persons considered the occurrence of these health problems to be very
The respondents were also asked to suggest ways to improve clinic services. The
suggestions are listed in Appendix D. The most common suggestions pertained to
decreasing the burden of frequent visits. These included establishing anticoagulation
clinics closer to their home, having blood drawn at local laboratories or decreasing the
frequencies of visits.
Construct validity was assessed by conducting a factor analysis and by examining
the correlations of items within and between the subscales. In conducting the factor
analysis, four factors were extracted using a principal-components method. These four
factors were subjected to a varimax rotation resulting in the factor structure shown in
Table 5-3. The items relating to perceived value, perceived benefits (threat reduction
operationalization) and perceived time costs comprised Factor 1 which accounted for
49.5% of the variance. Factor 2 consisted of the two items pertaining to perceived threat
—no participation. Factor 3 consisted of the two items representing perceived emotional
costs and Factor 4 was comprised of the two items for perceived threat-participation.
The factor analysis suggests that the subjects' perceptions of the benefits, costs
and value may not be conceptually distinct. However, the correlations for items within
each of these subscales were generally higher than correlations of items across subscales
(Table 5-4). This pattern of correlations suggests that these three subscales measure
distinct, albeit closely related, concepts.
The factor analysis also showed that the two items measuring perceived emotional
costs may be distinct from the perceived time costs. The correlations of the emotional
cost items with the time cost items ranged from 0.26 to 0.48 (Table 5-4) and the item-to-
total correlations of the two emotional cost items within the perceived costs scale score
were lower than the item-to-total correlations of the time cost items (see Appendix C for
further detail). Although the item-to-total correlations are lower for the emotional cost
items, these values are not exceptionally low (0.60 and 0.71). Cronbach's alpha for the
five-item perceived costs scale and the three-item time costs scale were both 0.79. Thus,
it may be appropriate to treat the emotional and time costs separately. Consequently, the
path analysis will be conducted treating the perceived costs as a single variable and as
separate emotional and time cost variables.
Rotated Factor Matrix
Q18 .. ,
Only factor scores in excess of ±0.30 are shown.
Correlations between variables
The path analysis began with an examination of the zero-order correlations
between the study subscales. The correlations are listed in Table 5-5. The direction and
magnitude of the correlations were consistent with the hypothesized relationships.
Correlation Matrix of Endogenous Variables
Threat Threat Benefit Benefit
-NP -P -SC -TR
Perceived threat— No participation
^ Perceived threat-Participation
^ Perceived benefits-Service component operationalization
** Perceived benefits-Threat reduction operationalization
The first global hypothesis was tested by calculating the ratio of chi-square to
degrees of freedom, TLl and AIC for the perceived value model. This model used the
threat reduction operationalization for perceived benefits due to its higher correlation
with the other endogenous variables. The goodness-of-fit indices along with the
standardized regression coefficients and the multiple correlation coefficient for each
dependent variable in the path model are presented in Figure 5-1. The ratio of chi-square
to degrees of freedom was 1 1 .96, the TLI was 0.922 and the AIC was 1 53.7. Although
the TLI was above the level designated for minimally acceptable fit (0.9), chi-square/
degrees of freedom was not below the 3:1 ratio recommended for acceptable fit. Hence,
Hypothesis 1 is rejected (i.e., the model exhibited unacceptable fit).
Discussions with the subjects regarding the clinic services suggested that their
perceptions of the benefits of the service may be influencing their perceptions of the costs
of using the serivce. This was consistent with the high correlation between perceived
benefits (threat reduction operationalization) and perceived costs (r = -0.67). Based upon
these findings, the perceived value model was revised to include a path fi-om perceived
benefits to perceived costs (Figure 5-2).
The goodness of fit of this revised model was compared to the goodness of fit
of the original conceptualization of the perceived value model. For the revised model, the
ratio of chi-square to degrees of freedom was 2.37, the TLI was 0.990 and the AIC was
57.31. Both the chi-square/degrees of freedom ratio and TLI meet the criteria for
acceptable fit, and the AIC for the revised model is substantially lower than the AIC for
the original model (57.3 versus 153.7). The chi-square difference for the two models was
significant (x"= 98.3, df = 1, p < 0.01). Hence, the "revised" perceived value model is a
substantial improvement over the original conceptualization. Furthermore, the variables
in this model explained 69% of the variance in perceived value and 68% of the variance
in behavioral intention.
The second global hypothesis posited that "removal of the conditional threat
variables from the perceived value model will not improve the goodness of fit of the
model." The paths between the conditional threat variables and perceived benefits were
constrained to zero to remove the influence of the conditional threat variables (Figure 5-
3). The model depicted in Figure 5-3 was compared to the "revised" model depicted in
Figure 5-2 to determine if removal of the perceived threat variables affected the goodness
of fit of the "revised" perceived value model.
Constraining the effect of the perceived threat variables to zero produced a model
which exhibited the following goodness of fit: chi-square/degrees of freedom rafio =
10.27, TLl = 0.934, AIC = 145.01. The squared multiple correlation coefficients for
perceived value and behavioral intention were essentially unchanged (0.69 and 0.68,
respectively). Constraining the paths to zero deleteriously affected the goodness of fit of
the model, yet did not affect the explained variance in perceived value and behavioral
intention. Therefore, Hypothesis 2 is not rejected (i.e., the goodness of fit did not
improve upon removal of the conditional threat variables).
The factor analysis suggested that Perceived Costs could be conceptualized as two
separate variables "time costs" and "emotional costs." To determine whether dividing the
single perceived cost variable into its constituent parts would produce better fit with the
data, the model in Figure 5-4 was tested. The ratio of chi-square to degrees of freedom
was 1 .99, the TLI was 0.992 and the AIC was 69.87. Compared to the model in Figure 5-
2, the model in Figure 5-4 had a worse fit according to AIC (69.87 versus 57.3 1), nearly
equivalent fit according to TLI (0.992 versus 0.990) and a better fit according to the ratio
of chi-square/degrees of freedom (1.99 versus 2.37). Additionally, the squared multiple
correlation coefficient was slightly higher in Figure 5-4 (0.71 versus 0.69). Although the
ratio of chi-square/degrees of freedom suggests that Figure 5-4 has a slightly better
goodness of fit, the chi-square difference test for Figures 5-4 and 5-2 was not significant
(X^= 4.56, df = 4, p = 0.34). The difference in AICs also suggests that dividing the
perceived costs into two variables increased the model complexity without a substantial
improvment in overall fit. Hence, the model in Figure 5-4 provides us with insight into
the potential relationship of the separate cost perceptions, but the model in Figure 5-2
exhibits the most parsimonious fit with the data.
Modifications on the above models were also tested. These models posited direct
paths between the perceived threat variables and perceived value as well as direct paths
from the benefits and costs perceptions to behavioral intention. None of these paths were
signficant. See Appendix B for these path models.
' ' '" ,
: - ; 1 f . ;
■"•";w-: ' : -
■; y J !
Goodness of Fit Indices
* TLI = Tucker-Lewis Index
t AIC = Akaike Information Criterion
°^ S ^ ^1 ^
—I , Z^ <N •
II II ^rp
II cii -u^
(D t+H II
T^ II en M ii
/ y \
\ w /
\ W /
H (N| 0^ fn
^ OS ^ -- "
^Ji. -^ H a
m o rj „
\ W /
m o "^ fN ^
CN| • ^ <j^ 00
II iL^ii cTso;
cr „ 1/3 lh HH
I Si T3
u ''J c3
Hypotheses for Model Components
This hypothesis stated, "the perceived value of the pharmaceutical care service
will have a direct, positive effect on the subjects' intentions to participate regularly in the
service." In the "revised" model (Figure 5-2), the standardized regression coefficient for
the path from perceived value to behavioral intention was 0.82 (p < 0.01). Hypothesis 3
is supported. v; "/* Cr ^
Hypothesis 4 •..:■.) ■ '• JC.' •
This hypothesis stated, "the perceived benefits of the pharmaceutical care service
will have a direct, positive effect on the perceived value of the pharmaceutical care
service." In the "revised" model (Figure 5-2), the standardized regression coefficient for
the path from perceived benefits to perceived value was 0.56 (p < 0.01). Hypothesis 4 is
This hypothesis stated, "the perceived costs of the pharmaceutical care service
will have a direct, negative effect on the perceived value of the pharmaceutical care
service." In the "revised" model (Figure 5-2), the standardized regression coefficient for
the path from perceived cost to perceived value was -0.34 (p < 0.01). Hypothesis 5 is
This hypothesis stated, "the perceived health threat-no participation will have a
direct, positive effect on the perceived benefits of the pharmaceutical care service." In
the "revised" model (Figure 5-2), the standardized regression coefficient for the path from
perceived threat—no participation to perceived benefits was 0.63 (p < 0.01). Hypothesis 6
This hypothesis stated, "the perceived health threat-participation will have a
direct, negative effect on the perceived benefits of the pharmaceutical care service." In
the "revised" model (Figure 5-2), the path from perceived threat—participation to
perceived benefits was -0.17 (p = 0.01). Hypothesis 7 is supported.
Hypothesis 1 was rejected indicating that the initial model did not exhibit
adequate fit with the data, however revising this model to include a direct path from
perceived benefits to perceived costs produced a model with acceptable fit. Hypothesis 2
was not rejected indicating that the removal of the perceived threat variables did not
enhance the fit between the model and data. Further revising the model to include
separate measures of time costs and emotional costs did not significantly improve the fit
between the model and data, although it explained a slightly higher amount of the
variance in perceived value.
Hypotheses 3 through 7, regarding the relationships of the individual variables,
were all supported. Additionally, the model in Figures 5-2 explained 69% of the
variance in perceived value and 68% of the variance in behavioral intentions. Hence, the
model in Figure 5-2 demonstrated the best overall fit with the data and explained a
substantial amount of variance in subjects' perceptions of the value of the pharmaceutical
care service and their intentions to use that service again. Although dividmg the
perceived costs into separate time and emotinal cost variables provided insight into how
these variables may individually relate to the other model components, it did not enhance
the goodness of fit of the perceived value model.
'>'T ji>lv *v^
The purpose of this chapter is to briefly review the purpose of the study, discuss
the results and describe the implications of this work for the practice of pharmacy.
Review of Study Objectives
To address the problems of drug-related morbidity and mortality, the profession of
pharmacy has embraced the concept of pharmaceutical care. Hepler and Strand defined
pharmaceutical care as "the responsible provision of drug therapy for the purpose of
achieving definite outcomes that improve a patient's quality of life (1990, p. 533). This
entails the pharmacist accepting responsibility for the outcomes of his patients and
engaging in activities that will enhance those outcomes. Many pharmacists have
implemented pharmaceutical care by offering structured medication-related education and
monitoring services to patients who were at risk of drug-related morbidity. Most
common are services for patients with asthma, diabetes, hypercholesterolemia or those
taking anti-coagulant medications.
Unfortunately, patient participafion has not been optimal. Tomeko and Strand
(1995), based upon their experiences with pharmaceutical care in Minnesota, suggest that
25% embrace pharmaceutical care initially, another 65% require more time to appreciate
it, while 5-10% never actively participate. The experiences of pharmaceutical care
projects at the University of Florida and the University of Washington have been similar.'
Unless patients actively participate in these services, the full benefits of pharmaceutical
care may not be achieved.
The purpose of this study was to investigate how patients' perceptions of the
benefits, costs and value of pharmaceutical care collectively influence their intentions to
use a pharmaceutical care service. Additionally, the extent to which the perceived threat
of specific health problems affect patients' perception of the benefits of pharmaceutical
care was examined. A "Perceived Value Model for Explaining Patients' Intentions to
Participate in Pharmaceutical Care" was developed based primarily upon the work of
Ronis (1992) and Zeithaml (1988). Within this model, the perceived value of a
pharmaceutical care service is conceptualized as a tradeoff between the perceived benefits
and perceived costs of using the pharmaceutical care service, wherein the perceived
benefits represent a perceived reduction in a specific health threat and the perceived costs
represent the time and emotional costs associated with using the service. The perceived
benefits of using the service, in turn, are influenced by the patient's perception of the
extent to which he is threatened by the health problem that the service is designed to
prevent or alleviate. This model was tested using survey data from 154 patients' enrolled
in a pharmacist-run anticoagulation clinic. Modifications to the model were made to
enhance the fit of the theoretical relationships with the data.
' This assertion is based upon the author's personal experience with projects at the University
of Florida as well as conversations with Dale Christensen at the University of Washington.
Discussion of Results
Optimizing the goodness-of-fit of the theoretical model
Four models were directly compared to identify the model which best fit the data.
The original conceptualization of the model exhibited poor overall fit and was revised to
include a direct path from perceived benefits to perceived cost (Figure 5-2). This
significantly improved the goodness-of-fit and produced a model whose parameters
would generally be considered acceptable (chi-square/degrees of freedom = 2.37, TLI =
0.990, AIC = 57.31). This model also explained 69% of the variance in perceived value
and 68% of the variance in behavioral intention. Additionally, when the conditional
threat variables were removed (Figure 5-3), the explained variance in perceived value and
behavioral intention remained the same while the goodness-of-fit worsened (chi-
square/degrees of freedom = 10.27, TLI = 0.934, AIC =145.01). Because the factor
analysis suggested that the perceived cost items represented separate constructs for time
and emotional costs, the model was revised to include these as separate variables (Figure
5-4). Although two of the indices for this model indicated slightly better fit than the
model in Figure 5-2 (chi-square/degrees of freedom = 1.99, TLI = 0.992), the chi-square
difference test indicated that the differences were not significant. Furthermore, the AIC
for the model in Figure 5-4 was higher than the AIC for the model in Figure 5-2
suggesting that the addition of the two parameters in Figure 5-4 worsened the overall
goodness of fit.
Breaking the perceived costs into two variables lends to our understanding of the
theoretical relationship between perceived benefits and perceived costs, even if the model
fit was not enhanced. The specific relationship between emotional costs and time costs as
depicted in Figure 5-4 was selected because it exhibited the best fit of numerous
alternatives tested (see Appendix B for some of the alternatives). However, it is possible
that this post-hoc finding is not indicative of the "true" relationship between these
Clearly, more research is needed on the relationship between perceived benefits,
monetary costs and various forms of nonmonetary costs before any firm conclusions be
drawn on the relationships between these variables and the conditions under which those
relationships exist. Discussion of the relationships between all of these constructs are
presented in the following sections. I
The Relationship of Benefits. Costs and Value
The perceived benefits of the pharmaceutical care service had a direct, positive
effect on the perceived value of the service and the perceived costs of participating in the
pharmaceutical care service had a direct, negative effect on the perceived value of the
service. In other words, people consider what they get from the service and what they
must sacrifice to obtain the service to determine if using the service is "worthwhile."
This is consistent with the models proposed by Dodds and Monroe (1985); Nau, Ried and
Lipowski (1997); Wood and Scheer (1996); and Zeithaml (1988).
Perceived benefits also had an indirect effect on perceived value by its effect on
perceived costs. The results of this study show that perceived benefits had a negative
influence on the perceived "nonmonetary" costs of participation. In other words, as
peoples' perception of the benefits increased, the perceived time and emotional costs
decreased. A substantial literature exists pertaining to the relationship of "monetary"
costs and perceived quality/benefits (see Rao and Monroe, 1989 for a review of this
topic). The general consensus is that under certain circumstances, a higher price may
lead people to believe that a product is of higher quality (Monroe and Krishnan, 1985;
Zeithaml, 1988). However examinations of the relationship between the perceived
"nonmonetary" costs of using a service and the perceived quality /benefits of the service
were not located in the extant literature. Jacoby, Szybillo and Beming's (1976) review of
the existing literature on time and consumer behavior suggests that people devote more
time to decision tasks that are more complex or more risky. However, they made no
mention of the relationship between perceived consumption time and perceptions of
benefits or quality.
It may be that peoples' perceptions of benefits, costs and value are not entirely
distinct. The factor analysis and an examination of the zero-order correlations among
these variables suggest that the constructs overlap. Perhaps, people do not judge the
appropriateness of their time expenditure without considering the benefits being derived
fi-om their behavior. Monroe and Dodds (1988) suggest that if people can infer quality
from price, then they may also infer price from quality. Zeithaml (1982) suggests that
when explicit pricing information is not available, people may judge the price of the
service after consumption. If these authors are correct in their assertions, then perhaps
people also judge the appropriateness of their time investment after experiencing the
benefits of a service.
The anticoagulation clinic data also showed that perceived benefits had a negative
effect on emotional costs which in turn had a positive effect on perceived time costs. In
other words, an increase in perceived benefits led to a decrease in the perceived emotional
costs and this decrease in emotional costs also led to a decrease in the perceived time
costs. However, the perceived benefits also had a direct effect on perceived time costs.
Perhaps, the perceived benefits influence perceived time costs by both a
cognitive and emotional route. Haynes (1990) suggests that waits for valued outcomes
seem shorter, and Chebat, Gelinas-Chebat and Filiatrault (1993) found that influencing
peoples' mood can influence their perception of time spent in queues. Thus, the subjects'
cognitive evaluation of the benefits of the pharmaceutical care service may directly
influence their assessment of the appropriateness of their time expenditure. They may
also have an affective response to the outcomes of the service encounter which appear as
the emotional costs. This in turn influences the perception of time.
The wordings of the two items pertaining to time costs may also have facilitated
the consideration of perceived benefits when evaluating the time costs. The items asked
the respondent to indicate whether the clinic visits were "too long" or "more often than
necessary." This judgment requires the respondent to compare the actual waiting time or
visit frequency to what they think it should be (i.e., their normative expectation).
Normative expectations for health-care services may be based not only on patients' prior
experience with the service, but also on their perceived vulnerability to a particular
health-related problem and the seriousness of that health-related problem. (Kravitz et al.,
1996). Thus, when someone has limited experience with a service, their judgment of the
appropriateness of the waiting time or visit interval may be based upon whether they feel
that their health-related problems are being dealt with effectively. Therefore, asking
whether the visits were "too long" or "more often than necessary" prompted the subjects
to consider the benefits of the service encounter when evaluating the costs.
A recent study on the relationship of perceived value and hospital choice may
provide further insight on the relationship between the perceived benefits and perceived
costs of health care services. Smith-Gooding (1995) attempted to predict peoples' choice
between hospitals based upon the perceived quality and sacrifice associated with using
each hospital. She added importance weightings to the consumers' perceptions of
hospital quality and sacrifice. Under major treatment situations, respondents assigned a
great deal of importance to the quality of the hospital, but for minor treatment situations,
respondents attached less importance to the quality ratings. Thus, when the "quality x
importance" score was low, the perceived sacrifice was more influential in predicting
hospital choice and when the "quality x importance" score was high, the perceived
sacrifice played a minimal role in predicting hospital choice. Perhaps, people pay more
attention to the sacrifice (e.g., costs) of a behavior when the perceived "quality x
importance" are low.
Smith-Gooding's conceptualization of a "quality x importance" score may be
roughly analogous to the way people evaluated the benefits in the anti-coagulation clinic.
The "Perceived Benefit - risk reduction" variable asked the respondents to indicate their
agreement as to whether meeting with the clinic provider on a regular basis decreases
their chance of experiencing two health problems. Their agreement may have depended
both on their assessment of the "abiUty of the provider" (i.e., perceived quality) and their
judgment of the importance of obtaining assistance in preventing these problems (which
may be influenced by their perceptions of the likelihood of experiencing the problems
and the severity of the problems). The results of this study showed that "Perceived
Benefits - risk reduction" was influenced by conditional perceptions of health threats,
however further work should be done to evaluate the interplay between perceived quality,
importance, and perceived benefits.
Finally, having identical response categories for each of these constructs and
measuring them simultaneously enhanced the likelihood of finding associations between
the constructs. It is unknown whether selecting alternative measurement strategies would
have altered the conclusions of this study, thus the conclusions regarding the associations
between perceptions of benefits, costs and value may only pertain to the operational
definitions used in this study.
Influence of Benefits. Costs and Value on Intention to Participate
The perceived value of the anticoagulation clinic services had a large influence on
the respondents' intentions to continue participation in the service (standardized
regression coefficient = 0.82). Tests of alternative models found that perceived benefits
and perceived costs did not have direct effects on behavioral intentions (see Appendix B),
rather the influence of perceived benefits and perceived costs was subsumed by perceived
value. Perceived benefits, costs and value, together, explained 68% of the variance in
behavioral intention (Figure 5-4). These findings are quite similar to those of Jones
(1993) who used a perceived value framework to study hospital choice. Within her
structural equation model, the standardized structural coefficient for the effect of
perceived value on behavioral intention was 0.86. While she did not directly assess the
influence of benefits and costs on behavioral intention, the pattern of correlations
between her measures of service quality, perceived value and behavioral intention were
consistent with the anti-coagulation clinic data.
Influence of Conditional Health Threat on Perceived Benefits
The subjects perceived the likelihood of their experiencing bleeding problems or
developing a clot to be high if they did not meet with the clinic provider on a regular
basis. They perceived the likelihood of developing these problems to be low if they met
with the provider on a regular basis. These conditional threat perceptions were both
associated with the perceived benefits of participating in the pharmaceutical care service,
particularly when perceived benefits was defined as perceived risk reduction. The higher
the perceived threat when not participating, the greater the perceived risk reduction.
Additionally, the lower the perceived threat when participating, the greater the perceived
The findings are consistent with those of Ronis (1992) who showed that peoples'
perceived susceptibility to gum disease when not flossing had a direct, positive effect on
the perceived benefits of flossing, and that perceived susceptibility to gum disease when
flossing had a direct, negative effect on the perceived benefits of flossing. Furthermore,
Ronis found that the influence of perceived susceptibility on benefits was stronger under
the "non-participation" condition. This is also consistent with the anticoagulation clinic
data. This may have occurred because the perceived likelihood of developing a health
' - * I'.
problem when engaging in the preventive behavior is uniformly low. Hence, the low
variation in the "Perceived threat—No participation" variable produced a low correlation
with the perceived benefits of the behavior. *" *
Ronis (1992) also found a direct effect of perceived susceptibility on behavior that
was not mediated by perceived benefits. Tests of alternative models using the
anticoagulation patient data did not find a significant direct effect of the perceived threats
on behavioral intention (see Appendix B). Additionally, constraining the paths from the
conditional threats to perceived benefits had almost no effect on the explained variance in
perceived value and behavioral intention. Thus, the effects of the perceived threats on
perceived value and behavioral intention was subsumed by the perceived benefits
Implications for Pharmacy Practice
The implementation of pharmaceutical care is perhaps the greatest challenge for
the profession of pharmacy as it enters the twenty-first century. A successful conversion
to this practice model will require not only a commitment on the part of pharmacists, but
also the cooperation of physicians, payers, and patients. This results of this study suggest
that patients' perceptions of the value of a pharmaceutical care service influence their
willingness to continue participation in that service. These perceptions of value are based
upon the patients' perceptions of whether meeting with the pharmacist reduces their
likelihood of experiencing the health problem that the service is designed to prevent or
ameliorate (i.e., the perceived benefits), as well as the time and emotional costs
associated with participation in the service. As the perceived benefits increase, and the
perceived costs decrease, the perceived value of the service is enhanced.
ft ■ — ■ '■
In this study, the perceived benefits of the service had a direct effect on the
perceived value of the service and also an indirect effect on perceived value by way of its
influence on the perceived "nonmonetary" costs of the service. If people perceive that the
service is very beneficial, they may be less concerned about the time and energy required
to participate. This suggests that optimizing patients' perceptions of the benefits of the
service will have a profound effect on their willingness to continue participation in the
service. If patients do not perceive the service to be beneficial, then they are unlikely to
view the service as beneficial no matter how low the perceived costs.
Pharmacists could help their patients see the benefits of participation in a number
of ways. They could begin by helping patients understand the risk of experiencing the
relevant health-related problems. For patients taking anticoagulant medications, the
problems may be the development a blood clot due to insufficient anti-coagulation, or
bleeding complications due to excessive doses of warfarin. This could be followed by an
explanation of how having the pharmacist monitor the blood levels of warfarin could
prevent these problems. If the patient has already experienced coagulation-related
problems due to insufficient monitoring, the pharmacist may be able to reinforce the
benefit of the pharmacy service by pointing out how the past problem could have been
avoided through more attentive monitoring. Conversely, if the patient has been taking the
medication for years with no overt problems, it may be difficult for the pharmacist to
convince the patient that the benefits of stringent monitoring are worth their time and
Nonetheless, patients may be experiencing health problems, yet do not attribute
them to sub-optimal drug therapy. For example, consider the patient taking a beta-
blocker who does not realize that his impotence is due to the drug, or the asthmatic who
does not realize that his frequent wheezing could be prevented through the use of an
inhaled corticosteroid. Thus, the pharmacist's initial challenge may come in helping the
patient understand the relationship between medication use and symptomatology. Once
this is accomplished, the pharmacist can then begin to help the patient see the connections
between pharmacy services, medication use and control of a disease.
An important point is that this study focused on patients who already had
experience with the pharmaceutical care service. Patients who have no experience with a
service are likely to base their judgments of potential value upon "extrinsic" cues
(Zeithaml, 1988). Extrinsic cues relevant to pharmaceutical care services may include:
the price of the service; recommendations of a family member, friend or physician;
advertising; and the image of the pharmacist or pharmacy. Monroe and Krishnan (1985)
suggest that a positive relationship exists between price and perceived quality, hence
providing a service for "free" may actually signal that it is not of high quality. Therefore,
pharmacists should inform their patients that they will bill the patient's insurer for their
services even if the pharmacist is unsure of whether the claim will be paid. This should
enhance the perceived benefits and value of pharmaceutical care.
Recommendations from a physician or friend are common sources of patient
expectations for physician services (Kravitz et al., 1996). Similarly, establishing good
relationships with physicians should facilitate referrals, and providing good care will
encourage patients to recommend the pharmacy to friends and family. Crane and Lynch
(1988) have found that people feel less at risk when using a personal referral to choose a
health care professional. Interviews with asthmatics regarding their interest in
pharmaceutical care services found that people would feel more comfortable enrolling in
a structured pharmaceutical care program if their physician supported their involvement
and many persons stated that they would use the service only upon physician referral
(Grainger-Rousseauet al., 1997). ~
Kravitz et al. (1996) found that patients' expectations for care can also be
influenced by media. Reading a newspaper article, or hearing a radio advertisement,
about new services that a pharmacy offers may stimulate some people to investigate these
services. For some people, higher levels of advertising also signal higher quality in a
product (Zeithaml, 1988). People may not only become more aware of the
pharmaceutical care services via advertisements, they may also perceive that the
pharmacy would not promote something that wasn't beneficial to their health.
However, it is unclear whether the public's image of a pharmacist is that of a
caring health professional or a business person. Research has typically found that
patients view pharmacists as purveyors of pills rather than health care professionals
(Schommer, 1997). This image will only change as pharmacists continue to provide
more patient-centered services and show a caring attitude towards their patients.
1^ :> ;> V. 100
n ^ Conclusion
Peoples' intentions to participate in pharmaceutical care are strongly influenced
by their perceptions of the value of the service (i.e., whether participation is worth their
time). The higher the perceived value, the greater their intention to participate. The
perceived value of pharmaceutical care is influenced by peoples' perceptions of whether
meeting with the pharmacist decreases the likelihood of their experiencing a health-
related problem (i.e., the perceived benefits), and by the time and emotional costs
incurred in meeting with the pharmacist. By increasing the perceived benefits or
minimizing the perceived costs of care, the perceived value of pharmaceutical care and
patient participation in pharmaceutical care can be enhanced.
r- -n ;->/'•
■'. 'H '■!■
Aday, L.A. & Andersen, R.M. (1974). A framework for the study of access to medical
care. Health Services Research . 9, 208-220.
Aiken, L.S., West, S.G., Woodward, C.K. & Reno, R.R. (1994). Health beliefs and
compliance with mammography-screening recommendations in asymptomatic
women. Health Psychology . 13. 122-129.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. InJ. Kuhl&
J. Beckmann (Eds.), Action-Control: From Cognition to Behavior (pp. 1 1-39).
Ajzen, 1. (1991). The theory of planned behavior. Organizational Behavior and
Human Decision Processes . 50, 1 79-2 1 1 .
Akaike, H. (1973). Factor analysis and AIC. Psvchometrika . 52, 317-332.
Alwin, D.F. & Hauser, R.M. (1975). The decomposhion of effect in path analysis.
American Sociological Review . 40, 37-47.
Andersen, R.M. (1995). Revisiting the behavioral model and access to medical care:
Does it matter? Journal of Health and Social Behavior . 36, 1-10.
Andersen, R.M. & Andersen, O.W. (1967). A Decade of Health Services . Chicago, IL:
University of Chicago Press.
Andersen, R.M. & Newman, J.F. (1973). Societal and individual determinants of
medical care utilization in the United States. Millbank Memorial Fund
Quarterly Journal . 51. 95-124.
American Pharmaceutical Association. (1996). National Pharmacy Consumer Survey .
Washington, DC: Author.
Babukus, E. & Mangold, W.G. (1992). Adapting the SERVQUAL scale to hospital
services: An empirical investigation. Health Services Research . 26(6), 767-
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review . 84, 119-215.
Becker, M.H. (1974). The health belief model and personal health behavior. Health
Education Monographs . 2(4), 324-508.
Becker, M.H., Drachman, R.H. & Kirsht, J. P. (1974). A new approach to explaining
sick-role behavior in low-income populations. American Journal of Public
Health, 64,205-216. ^
Becker, M.H. & Maiman, L.A. (1975). Sociobehavioral determinants of compliance
with health and medical care recommendations. Medical Care . 13, 10-24.
Becker, M.H., Maiman, L.A., Kirscht, J.P., Haefner, D.P. & Drachman, R.H. (1977).
The Health Belief Model and prediction of dietary compliance: A field
experiment. Journal of Health and Social Behavior . 18. 348-366.
Becker, M.H. & Rosenstock, l.M. (1987). Comparing social learning theory and the
Health Belief Model. In W.B. Ward (Ed.), Advances in Health Education and
Promotion (Vol. 2, pp. 1 15-129). Greenwich, CT: JAl Press.
Bentler, P.M., & Bonett, D.G. (1980). Significance tests and goodness of fit in the
analysis of covariance structures. Psychological Bulletin . 88, 588-606.
Bice, T.W. & White, K.L. (1969). Factors related to the use of health services: An
international comparative study. Medical Care . 7, 124-133.
Blalock, S.J., DeVellis, B.M., Afifi, R.A. & Sandler, R.S. (1990). Risk perceptions and
participation in colorectal cancer screening. Heahh Psychology . 9(6), 792-806.
Bollen, K.A. & Long, J.S. (1993). Testing Structural Equation Models . Newbury Park,
CA: Sage Publications.
Bolton, R.H. & Drew, J.H. (1991). A multistage model of customers' assessments of
service quality and value. Journal of Consumer Research . 17, 375-384.
Boulding, W., Kaira, A. & Staelin, R. (1995). The quality double whammy. Working
Paper, Duke University, Durham, NC.
Boulding, W., Kalra, A., Staelin, R. & Zeithaml, V.A. (1993). A dynamic process model
of service quality: From expectations to behavioral intentions. Journal of
Marketing Research . 30, 7-27.
Brooks, C.H. (1973). Associations among distance, patient satisfaction, and utilization of
two types of inner-city clinics. Medical Care . 1 1, 373-383.
Brown, CM. (1994). An assessment of ethnic differences in drug use decision making
among African American and White American hypertensive patients: Implications
for hypertension management, (Doctoral dissertation, University of Florida,
Caranasos, G.J., Stewart, R.B. & Cluff, L.E. (1974). Drug-induced illness leading to
hospitalization. Journal of the American Medical Association . 229, 1043-1044.
Carlson, E.R. (1956). Attitude change through modification of attitude structure. Journal
of Abnormal and Social Psychology . 52, 256-261.
Carmel, S., Shani, E. & Rosenburg, L. (1994). The role of age and an expanded Health
Belief Model in predicting skin cancer protective behavior. Health Education
Research . 9, 433-447.
Carmines, E.G. & Mclver, J.P. (1981). Analyzing models with unobserved variables. In
G.W. Bohmstedt & E.F. Borgatta (Eds.), Social Measurement: Current Issues ,
(pp. 78-88). Beverly Hills: Sage.
Chang, B.L. (1984). The effects of systematically varying components of nursing care on
satisfaction in elderly ambulatory women. Western Journal of Nursing Research .
Chebat, J-C, Gelinas-Chebat, C. & Filiatrault, P. (1993). Interactive effects of musical
and visual cues on time perception: An application to waiting lines in banks.
Perceptual and Motor Skills . 77, 995-1020.
Chewning, B. & Sleath, B. (1996). Medication decision-making and management: A
client-centered model. Social Science and Medicine . 42(3), 389-398.
Connor, M. & Norman, P. (1994). Comparing the Health Belief Model and the Theory
of Planned Behaviour in health screening. In D. Rutter, & L. Quine (Eds.),
Social Psychology and Health: European Perspectives (pp. 1-24). Brookfield,
Crane, F.G. & Lynch, J.E. (1988). Consumer selection of physicians and dentists:
An examination of choice criteria and cue usage. Journal of Health Care
Marketing, 8(3), 16-19.
*?'»«■ i « 104
Cronin, J.J. & Taylor, S.A. (1992). Measuring service quality: A reexamination and
extension. Journal of Marketing . 56, 55-68.
Cronin, J.J & Taylor, S.A. (1994). SERVPERF Versus SERVQUAL: Reconciling
performance-based and perceptions-minus-expectations measurement of service
quality. Journal of Marketing . 58, 125-131.
Davies, A.R. & Ware, J.E. (1988). Involving consumers in quality of care assessment.
Health Affairs . (Spring), 33-48.
Dodds, W.B. & Monroe, K.B. (1985). The effect of brand and price information on
subjective product evaluations. Advances in Consumer Research . 12, 85-90.
Donabedian, A. (1980). Explorations in Quality Assessment and Monitoring: Vol 1.
The Definition of Quality and Approaches to its Assessment . Arm Arbor, MI:
Health Administration Press.
Donabedian, A. (1983). Quality assessment and monitoring: Retrospect and prospect.
Evaluation and the Health Professional . 6(3), 363-375.
Duncan, O.D. (1971). Path analysis: sociological examples (addenda). In H.M. Blalock,
Jr. (Ed.), Causal Models in the Social Sciences (pp. 136-138). Chicago: Aldine-
Eagly, A.H. & Chaiken, S. (1993). The Psvchologv of Attitude.s . Orlando: Harcourt,
Edwards, W. (1954). The theory of decision making. Psychological Bulletin . 51,
Edwards, W. & Newmann, J.R. (1982). Multiattribute Evaluation . Beverly Hills: Sage.
Fabrega, H. & Roberts, R.E. (1972). Social-psychological correlates of physician use
by economically disadvantaged Negro urban residents. Medical Care . 10,
Ferketich, S. (1991). Focus on psychometrics: Aspects of item analysis. Research
in Nursing & Health . 14,165-168.
Fincham, J.E. & Wertheimer, A.I. (1987). Predictors of patient satisfaction with
pharmacy services in a Health Maintenance Organization. Journal of
Pharmaceutical Marketing & Management . 2(2), 73-88.
Fishbein, M. & Ajzen, I. (1975). Beliefs. Attitude. Intention, and Behavior: An
Introduction to Theory and Research . Reading, MA: Addison- Wesley.
Fletcher, H.J., Ibrahim, S.A. & Speight, N. 1990. Survey of asthma deaths in the
Northern region, 1970-85. Archives of the Disease of Childhood . 65, 163-167.
Francis,V., Korsch, B.M. & Morris, M.J. (1969). Gaps in doctor-patient communication.
Patients' response to medical advice. The New England Journal of Medicine . 280,
Gagnon, J. P. (1994). Consumers' views toward pharmacy. Journal of Pharmaceutical
Marketing & Management . 8(4), 87-96.
Goldman, L., Freidin, R., Cook, E.F., Eigner, J. & Grich, P. (1982). A multivariate
approach to the prediction of no-show behavior in a primary care center.
Archives of Internal Medicine . 142, 563-567.
Grainger-Rousseau, T.J., Miralles, M.A., Hepler, CD., Segal, R., Doty, R.E. &
Ben- Joseph, R. (1997). Therapeutic outcomes monitoring: Application of
Pharmaceutical Care Guidelines to Community Pharmacy. Journal of the
American Pharmaceutical Association , (in press).
Grymonpre, R.E., Mitenko, P.A., Sitar, D.S., Aoki, F.Y. & Montgomery, P.R. (1988).
Drug-associated hospital admissions in older medical patients. Journal of the
American Geriatrics Society . 36, 1092-1098.
Harrison, J.A., Mullen, P.D. & Green, L.W. (1992). A meta-analysis of studies of the
Health Belief Model with aduhs. Health Education Research . 7, 107-1 16.
Hartman, I. & Im, J.H. (1992). Evaluation of a role for a clinical pharmacist in asthma
ambulatory care. Journal of Allergv & Clinical Immunologv . 89(1), 188.
Hauser, J.R. & Shugan, S.M. (1983). Defensive marketing strategies. Marketing Science .
Hauser, J.R. & Simmie, P. (1981). Profit maximizing perceptual positions: An integrated
theory for the selection of product features and price. Management Science .
Hauser, J.R. & Urban, G. (1986). The value priority hypotheses for consumer budget
plans. Journal of Consumer Research . 12(March), 446-462.
Haynes, P.J. (1990). Hating to wait: Managing the final service encounter. Journal of
Services Marketing . 4(4), 20-26.
Haynes, R.B. (1976). A critical review of the "determinants" of patient compliance with
therapeutic regimens. In D.L. Sackett & R.B. Haynes (Eds.), Compliance with
Therapeutic Regimens . Baltimore, MD: Johns Hopkins University Press.
Headley, D.E. & Miller, S.J. (1993). Measuring service quality and its relationship to
future consumer behavior. Journal of Health Care Marketing . 13(4), 32-41.
Hepler, CD. & Grainger-Rousseau, T.J. (1995). Pharmaceutical care versus traditional
drug treatment. Drugs . 49(1), 1-10.
Hepler, CD. & Strand, L.M. (1990). Opportunities and responsibilities in pharmaceutical
care. American Journal of Hospital Pharmacy . 47, 533-543.
Holbrook, M.B. & Corfman, K.P. (1985). Quality and value in the consumption
experience: Phaedrus rides again. In J. Jacoby & J.C Olson (Eds.), Perceived
Ouality. How Consumers View Stores and Merchandise , (pp. 31-56), Lexington,
MA: Lexington Books.
Hulka, B.S., Zyzanski, S.J, Cassel, J.C. & Thompson, S.J. (1971). Satisfaction with
medical care in a low income population. Journal of Chronic Diseases . 24,
Hutchinson, R.A., Lewis, R.K. & Hatoum, H.T. (1990). Inconsistencies in the drug use
process. DICP . 24, 633-636.
Institute of Medicine (1990). Medicare: A strategy for quality assurance. 2 vols (p. 21),
Washington, DC: National Academy Press.
Jacoby, J., Szybillo, G.J. & Berning, CK. (1976). Time and consumer behavior: An
interdisciplinary overview. Journal of Consumer Research . 2, 320-339.
Janz, N.K. & Becker,M.H. (1984). The Health Belief Model: A decade later. Health
Education Quarterly . 11, 1-47. .
Johnson, J.A.& Bootman, J.L. (1996). Drug-related morbidity and mortality. Annals
of Internal Medicine . 155, 1949-1956.
Joint Commission for the Accreditation of Healthcare Organizations. (1995). Using
patient input in a cycle for performance improvement. Journal of Ouality
Improvement . 21(2), 90.
Jones, S.I. (1993). Consumers' perceptions of sacrifice, service quality, and value
in the health care industry. (Doctoral dissertation, Texas A&M, College Station).
Jones, P.K., Jones, S.L. & Katz, J. (1987). Improving compliance for asthmatic patients
visiting the emergency department using a Health Belief Model intervention.
Journal of Asthma . 24(4'). 199-206.
Joreskog, K.G. (1993). Testing structural equation models. In K.A. Bollen &
J.S. Long (Eds.), Testing Structural Equation Models , (pp. 294-316),
Newbury Park, CA: Sage Publications.
Kaplan, S.H. & Ware, J.E. (1989). The patient's role in health care and quality
assessment. In N. Goldfield & D.B. Nash (Eds.), Providing Quality Care:
The Challenge to Clinicians (pp. 29-65). Philadelphia: American College
Klohn, L.S. & Rogers, R.W. (1991). Dimensions of the severity of a health threat: The
persuasive effects of visibility, time of onset, and rate of onset on young women's
intentions to prevent osteoporosis. Health Psycholog y. 10(5), 323-329.
Korsch, B.M.. Gozzi, E.K. & Francis, V. (1968). Gaps in doctor-patient communication.
1. Doctor-patient interaction and patient satisfaction. Pediatrics . 42(5),
Kravits, J. (1975). The relationship of attitudes to discretionary physician and dentist use
by race and income. In R. Andersen, J. Kravits, & O.W. Andersen (Eds.), Equity
in Health Services (pp. 75-89). Cambridge, MA: Ballinger Publishing Co.
Kravitz, R.L., Callahan, E.J., Patemiti, D., Antonius, D., Dunham, M. & Lewis, C.E.
(1996). Prevalence and sources of patients' unmet expectations for care.
Annals of Internal Medicine . 125. 730-737.
Langlie, J.K. (1977). Social networks, health beliefs, and preventative health behavior.
Journal of Health and Social Behavior . 18, 244-260.
Lau, R.R., Harman, K.A. & Ware, J.E. (1986). Health as a value: Methodological and
theoretical considerations. Health Psychology . 5, 25-43.
Leape, L.L., Lawthers, A.G., Brennan, T.A. & Johnson, W.G. (1993). Preventing
medical injury. Quality Review Bulletin . 17, 144-149.
Linn, L.S. & Greenfield, S. (1982). Patient suffering and patient satisfaction among the
chronically ill. Medical Care . 20, 425-431.
Locker, D.& Dunt, D. (1978). Theoretical and methodological issues in sociological
studies of consumer satisfaction. Social Science and Medicine . 12, 283.
MacKeigan, L.D. & Larson, L.N. (1989). Development and validation of an instrument
to measure patient satisfaction with pharmacy services. Medical Care . 27(5),
522-536. ^ .
Mackowiak, J.l. & Manasse, H.R. (1988). Expectations for ambulatory services in
traditional and office-practice pharmacies. American Journal of Hospital
Pharmacy . 41. 1140-1146.
Manasse, H.R. (1984). Medication use in an imperfect world, I: Drug misadventuring as
an issue of public policy. American .lournal of Hospital Pharmacy . 46, 929-44.
Marquis, M.S., Davies, A.R. & Ware, J.E. (1983). Patient satisfaction and change in
medical care provider: A longitudinal study. Medical Care . 21(8), 821-829.
McGee, .1. & Knutson, D. (1994). Health care report cards: What about consumers'
perspectives? Journal of Ambulatory Care Management . 17(4), 1-14.
McKenney, J.M. & Harrison, W.L. (1976). Drug related hospital admissions. American
Journal of Hospital Pharmacy . 33, 792-795.
McMillan, J.R. (1987). Measuring consumer satisfaction to improve quality of care.
Heahh Progress . 68(2), 54-55.
Monroe, K.B. & Dodds, W.B. (1988). A research program for establishing the validity of
the price-quality relationship. Journal of the Academv of Marketing Science .
Monroe, K.B. & Krishnan, R. (1985). The effect of price on subjective product
evaluations. In J Jacoby & J. Olson (Eds.), Perceived Quality (pp. 209-302),
Lexington, MA: Lexington Books.
Mullen, P.D., Hersey, J.C. & Iverson, D.C. (1987). Health behavior models compared.
Social Science and Medicine . 24. 973-981 .
Nau, D.P. & Lipowski, E. (1995). The status of pharmaceutical care and patient
satisfaction among asthmatics in Florida . Paper presented at the American
Pharmaceutical Association meeting, Orlando, Florida.
Nau, D.P., Lipowski, E., & Ried, L.D. (1997). What makes patients think that their
pharmacists' services are of value? Journal of the American Pharmaceutical
Association, NS37(1), 91-98.
Nelson, E.C., Rust, R.T., Zahorik, A., Rose, R.L., Batalden, P. & Siemanski, B.A. (1992).
Do patient perceptions of quality relate to hospital financial performance?
Journalof Health Care Marketing . (December), 6-13.
Nunnally, J.C. (1978). Psychometric Theory . New York: McGraw-Hill.
Oliver, R.L. (1980). A cognitive model of the antecedents and consequences of
satisfaction decisions. Journal of Marketing Research . 17, 460-469.
Oliver, R.L. (1993). Cognitive, affective, and attribute bases of the satisfaction response.
Journal of Consumer Research . 20, 418-430.
Oliver, R.L. (1996). Varieties of value in the consumption satisfaction response.
Advances in Consumer Research . 23, 143-147.
Oliver, R.L. & Berger, P.K. (1979). A path analysis of preventive health care decision
models. Journal of Consumer Research . 6, 1 13-122.
Parasuraman, A., Berry, L.L. & Zeithaml, V.A. (1991). Refinement and reassessment
of the SERVQUAL scale. Journal of Retailing . 67, 420-450.
Parasuraman, A., Zeithaml, V.A. & Berry, L.L. (1985). A conceptual model of service
quality and its implications for future research. Journal of Marketing . 49, 41-50.
Payne, J.W. (1982). Contingent decision behavior. Psychological Bulletin. 92,
Peak, H. (1955). Attitude and motivation. In M.R. Jones (Ed.), Nebraska Svmposium
of Motivation (pp. 149-188). Lincoln: University of Nebraska Press.
Pearce, T., O'Shea, J.S. & Wessen, A.F. (1979). Correlations between appointment
keeping and reorganization of hospital ambulatory pediatric services. Pediatrics .
Rao, A.R. & Monroe, K.B. (1989). The effects of price, brand name and store name on
buyers' subjective product assessments: An integrative review. Journal of
Marketing Research . 26r3V 351-357.
■■- ' no
Reuben, D.B., Posey, E. Hays, R.D. & Lim, M.E. (1994). Predictors of patient refusal
to participate in ambulatory-based comprehensive geriatric assessment. Journal
of Gerontology . 49(5), M209-M215.
t ' '■ -.
Ronis, D.L. (1992). Conditional health threats: health beliefs, decisions, and
behaviors. Health Psychology . 11(2), 127-134.
Ronis, D.L. & Harel, Y. (1 989). Health beliefs and breast examination behaviors:
Analyses of linear structural relations. Psychology and Health . 3, 259-285.
Rosenburg, M.J. (1956). Cognitive structure and attitudinal affect. Journal of Abnormal
and Social Psychology . 53, 367-372.
Rosenstock, l.M. (1966). Why people use health services. Milbank Quarterly . 44(3).
Rust, R.T., Inman, J.J. & Zahorik, A. (1995). A Bayesian model of quality and customer
retention . Paper presented at the Association for Consumer Research Annual
Meeting, Boston, MA.
Salant, P. & Dillman, D.A. (1994). How to Conduct Your Own Survey . New York:
John Wiley & Sons, Inc.
Sawyer, A., & Dickson, P. (1984). Psychological perspectives on consumer response to
sales promotion. In K. Jocz (Ed.), Research on Sales Promotion: Collected Papers ,
(pp. 84-92). Cambridge, MA: Marketing Science Institute.
Schering Laboratories. (1992). Schering Report XIV. Improving Patient Compliance: Is
There a Pharmacist in the House? Kenilworth, NJ: Schering Laboratories.
Schommer, J.C. (1997). Patients' expectations and knowledge of patient counseling
services that are available from pharmacies. American Journal of Pharmaceutical
Education (in press).
Schwarzer, R. (1992). Self-efficacy in the adoption and maintenance of health behaviors:
Theoretical approaches and a new model. In R. Schwarzer (Ed.), Self-efficacy:
Thought Control of Action Tpp. 1-19). London: Hemisphere.
Sherbourne, CD., Hays, R.D., Ordway, L., DiMatteo, M.R. & Kravitz, R.L. (1992).
Antecedents of adherence to medical recommendations: Results from the Medical
Outcomes Study. Journal of Behavioral Medicine . 13(5), 447-467.
■ - 111
Smith, H.A. (1992). Elucidating relationships among patronage variables. In H.A. Smith
& S.J. Coons (Eds), Marketing Pharmaceutical Services (pp. 149-156).
Binghampton, NY: The Haworth Press, Inc.
Smith, H.A. & Coons, S.J. (1993). Patron experience and satisfaction with
pharmaceutical services. Journal of Pharmaceutical Marketing & Management .
Smith-Gooding, S.K. (1995). Quality, sacrifice, and value in hospital choice. Journal of
Heahh Care Marketing . 15(41. 24-31.
Spencer, E. (1974). The attitudes of ambulatory patients toward a hospital-based
pharmacy service: The patient as consultant. Drug Intelligence and Clinical
Pharmacv . 8. 710-716.
Stanton, A.L. (1987). Determinants of adherence to medical regimens by hypertensive
patients. Journal of Behavioral Medicine . 10(4), 377-394.
Starkenburg, R.J., Rosner, F. & Crowley, K. (1988). Missed appointments among
patients new to a general medical clinic. New York State Journal of Medicine .
Strand, L.M., Cipolle, R. & Morley, P.C. (1990). Drug related problems: their structure
and function. DICP, 24, 1093-1097.
Sternberg, L. (1990). From velleity to specific plans: How planning affects attitude,
intention, behavior relations. (Doctoral dissertation, Purdue University,
W. Lafayette, IN).
Sullivan. S.D., Kreling, D.H. & Hazlet, T.K. (1990). Noncompliance with medication
regimens and subsequent hospitalization: A literature analysis and cost of
hospitalization estimate. Journal of Research in Pharmaceutical Economics .
Tanaka, J.S. (1993). Multifaceted comparisons of fit in structural equation models.
In K.A. Bollen & J.S. Long (Eds.), Testing Structural Equation Models
(pp. 10-39), Newbury Park, CA: Sage Publications.
Taylor, S.A. (1994). Distinguishing service quality from patient satisfaction in
developing heakh care marketing strategies. Hospital & Health Services
Administration . 39(2), 22 1 -236.
Teas, R.K. (1993). Expectations, performance evaluation and consumers' perceptions of
quality. Journal of Marketing . 57, 18-34.
Tomeko, M.A. & Strand, L.M. (1995). Comprehensive Pharmaceutical Care . Kansas
City, MO: Marion Merrell Dow, Inc.
Tucker, L.R. & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor
analysis. Psychometrika . 38, 1-10.
van der Plight, J. (1994). Risk appraisal and health behaviour. In D. Rutter, & L. Quine
(Eds.). Social Psychology and Health: European Perspectives (pp. 131-151).
Brookfield, VT: Avebury.
Wallston, K.A. & Wallston, B. (1981). Health locus of control scales. In H. Lefcourt
(Ed.), Research with the Locus of Control Construct (Vol. 1, pp. 70-81).
New York: Academic Press.
Wan, T.T.H. & Soifer, S.J. (1974). Determinants of physician utilization: A causal
analysis. Journal of Health and Social Behavior . 15, 100-108.
Ware, J.E., Davies-Avery, A., Stewart, A.L. (1978). The measurement and meaning of
patient satisfaction. Health & Medical Care Services Review . 1(1), 1-14.
Ware, J.E., Snyder, M.K., Wright, W.R. & Davies, A.R. (1983). Defining and measuring
patient satisfaction with medical care. Evaluation and Program Planning . 6,
Ware, J.E., Wright, W.R., Snyder, M.K. & Chu, G.C. (1975). Consumer perceptions of
health care services: Implications for the academic medical community. Journal
of Medical Education . 50, 839-848.
Wiederholt, J. & Rosowski, P.O. (1996). Antecedents of expectations for pharmacist
information services measured in naturalistic settings. Marketing Theory and
Applications . 7, 296.
Wood, CM. & Scheer, L.K. (1996). Incorporating perceived risk into models of
consumer deal assessment and purchase intent. Advances in Consumer Research .
Woodside, A.G., Frey, L.L. & Daly, R.T. (1989). Linking service quality, customer
satisfaction, and behavioral intention. Journal of Health Care Marketing . 9(4),
Zeithaml, V.A. (1982). The acquisition, meaning, and use of price information by
consumers of professional service. In R. Bush & S. Hunt (Eds.). Marketing
Theory: Philosophy of Science Perspectives (pp. 120-134). Chicago: American
Zeithaml, V.A. (1988). Consumer perceptions of price, quality, and value: A means-end
model and synthesis of evidence. Journal of Marketing . 52, 2-22.
Zeithaml, V.A., Berry, L.L. & Parasuraman, A. (1996). The behavioral consequences
of service quality. Journal of Marketing . 60. 31-46.
TV/- J ■.'."■ ', " ./»'
This survey will help us evaluate the services provided by the Pharmacotherapy
(Coag) Clinic at the VA. We want to know if you think attending this clinic is
worthwhile and if there is anything that the VA can do to improve your care.
I. This first section helps us understand your experience with taking your
anticoagulant medication (i.e., warfarin/coumadin).
1 . During the past year, did you talk with your physician about
your warfarin (Coumadin) prescription? Q Yes Q No
2. During the past year, have you gone to the emergency center
because of bleeding problems or a blood clot? Q Yes Q No
3. Dunng the past year, have you been hospitalized because of
bleeding problems or a blood clot? Q Yes Q No
4. How long have you been taking warfarin (Coumadin)?
Q 0-3 months Q 4-1 2 months Q 1 -2 years Q 3 or more years
II. The following statements ask how you would like to receive services from the
Pharmacotherapy (Coag) Clinic at the VA Please check the one statement
that best describes the way you would want to receive services.
If I could get my warfarin prescription without coming to this clinic,
I would prefer to ...
a) not meet with the clinic provider anymore.
b) meet with the clinic provider only when I have
a question about my health or medication.
c) continue to meet with the clinic provider
on a regular basis.
Please check the box that best describes your agreement
with the following statements.
about how to take warfarin is worth
5. Talking with the provider in the clinic /^ /^ /"^ y^ /'^
about how to take warfarin is worth I I I I I
the time it takes □ □ q q q
6. Talking with the clinic provider about
my blood levels of warfarin is worth
the time it takes ■?..."!*"' □ q q q q
7. Meeting with the clinic provider on a
regular basis is worth the time it takes. ... □ Q □ □ Q
8. Meeting with the clinic provider about my
warfarin takes too long q q q q q
9. I ann expected to visit the clinic
more often than is necessary q q q q q
10. I am expected to visit the clinic at
times that are inconvenient for me q q q q q
11.1 feel uncomfortable talking with the
clinic provider about my health problems. . □ □ □ □ □
1 2. Talking with the provider about my
health and warfarin makes me stressed. . . □ □ □ □ □
1 3. Meeting with the clinic provider on a
regular basis decreases my chances of
forming a clot in my blood □ q q q q
14. Meeting with the clinic provider on a
regular basis decreases my chance of
having problems with my warfarin □ □ □ q q
IV. Please check the box that indicates how beneficial you think
some of the clinic services are. , .
1 5. How beneficial is it to have
the clinic provider...
a) explain how to take warfarin.
b) explain what foods to avoid
when taking warfarin
c) monitor your blood levels
d) discuss whether you have
had problems with bleeding.
e) discuss whether you have
had problems with bruising.
Not Somewhat Fairly Very
Beneficial Beneficial Beneficial Beneficial
, V i i . ^ *
fi .. . ■♦<■•■
This section asks you how likely it is that you will expenence health-related
problems whether or not you meet with the provider in the VA clinic
regarding your warfarin. Please check the box that best indicates the
likelihood that you will experience these problems.
16. If you do not meet with the provider on a
regular basis, what is the likelihood of your
forming a clot in your blood?
1 7. If you meet with the provider on a regular
basis, what is the likelihood of your forming
a clot in your blood?
□ Q Q Q Q
□ Q Q a a
18. If you do not meet with the provider on a / A /^ ^'^ ^
regular basis, what is the likelihood of your I I I I I
experiencing bleeding problems? □ □ q q q
1 9. If you meet with the provider on a regular
basis, what is the likelihood of your
experiencing bleeding problems? □ □ q q q
Vl. Please indicate your agreement with the
20. Developing a blood clot is a very serious health problem.
□ strongly Agree Q Agree □ Neutral □ Disagree □ Strongly Disagree
21 . Developing bleeding complications from warfarin
is a very serious health problem.
□ strongly Agree □ Agree □ Neutral □ Disagree Q Strongly Disagree
Vll. The following questions are about you.
A. Gender; QMale □Female
C. Ethnic Origin:
□ White (not Hispanic) □ Hispanic □ Native American
□ Black (not Hispanic) □ Asian or Pacific Islander
/ H— 1
-a ^ ..
\ w /
^ ^ (N OO 00
ii o.^ II ^n
^41 •? ^ S
O O OX)
CS o °
■■^ „^ "-I
T-l ^ <U
>^ '-3 vr%
- i .
i * ■■) ?
•^ m r^
<N 00 oo
■— 3 CO
• APPENDIX C
INTER-ITEM AND ITEM-TO-TOTAL CORRELATIONS
Perceived Benefits - Service Component Operational ization
Q15C Q15D Q15E
0.62 0.90 1.00
0.77 0.92 0.91
QIO Qll Q12
0.43 0.55 1.00
0.83 0.60 0.71
SUBJECTS' COMMENTS ON CLINIC SERVICES
1. I think the service is great. I want to thank ail of the providers, they are doing a
great job. Service is very good and personal, very good and helpful.
2 I think it's very good and I have no complaints. Everybody here have been very
nice and helpful.
3. Recommend more frequent visits.
4. I'm very happy.
5. Excellent pharmacy. . ,
7. I live 1 00 miles from this facility and visits seem too often to me.
8. I was told by a Dr. Murphy six months ago I would get help for my hearing
problem and mentioned to several people since, but still nothing said or done.
9. Basically, I am happy with the clinic. I find it hard to understand the frequency of
required visits. I have a friend who takes Coumadin as a result of having had a
pulmonary embolism. His dosage is about the same as mine however his private
physician checks his INR only 2 times a year. Which frequency, his or mine, is
correct. I don't know but surely one or the other is off. Too little in his case or
too often in mine. . iv"" '. /
10. I would like to say the way the clinic is run now is very helpful. The staff is so
helpful and they do a good job. I hope the VA will continue this way of
operations and help.
11. My overall assessment is the clinic has been run very well and has been extremely
12. I would like to see a doctor on a scheduled visit. So far I have not been seen by a
doctor at the VA.
13. Would like the VA to allow vets to receive greater than a one month supply of
medications. Being limited to a one month supply makes life difficult for vets
who travel. Would also like to be able to have all of my clinic visits on the same
day. I live 250 miles away, and was told that I couldn't schedule all of my clinics
on the same day because some of the clinics are booked on the days when the
other clinics have openings. I don't like having to travel 1500 miles in one week
to visit three different clinics at the same VA hospital. If it wasn't for the free
medications, I would have nothing to do with the VA.
14. Decrease the time it takes for the lab results to get to the clinic.
15. Pharmacy has always been very good to me by telling me why I take a certain
medication and the benefits or side effects. I attribute an awdul lot of my well-
being and longevity to your service. Thank you.
16. The services are good. The staff are very caring and concerned with our
problems. I could not ask for better care. .
17. I think your clinic is wonderful. My husband had an appointment in renal clinic
two weeks ago. He has been going to the clinic for about five years. We have
seen many Doctors in the clinic, love everyone, also think highly of Marge the
nurse that runs the clinic, however the last visit we saw a Dr. Abraham, and was
greatly disappointed in the way he "solved" my husband's high blood pressure
meds - He looked at the list of meds and told me just increase the med Doxasozin
8mgs by Vi tab more daily. He did not explain why nor did he write a new script
for my husband. I knew I had an appointment with the Pharmacotherapy Clinic,
and I knew 1 could speak with them. They helped me. My husband has had such
good care at this hospital. 1 believe the doctors are outstanding. I do hope Dr.
Abraham moves on - I'm sure he'll find his calling at some other hospital. All of
the other doctors have been truly outstanding. I wish I could give them all a raise.
18. I like reordering my medications by phone. It saves me time, and travel. Since I
live in Ocala this is helpful to me. But I think meeting my provider on a regular
basis gives me peace of mind about my condition.
1 9. Service is excellent, but if it would be possible to have my blood checked at
Daytona Beach Clinic it would be much easier for me. I am 74 years old and the
ride is very tiring for me. Thank-you.
20. Too many visits!
21. I think the services provided are very helpful and adequate. Thank-you.
22. I would prefer for a local lab to draw the blood to save a long drive.
. —■% ■> ■ '■■ . ' I
23. The phone answering machine is annoying. Don't know if message is heard by the
right people and my doctor had such a hard time getting through to arrange
transportation that 1 ended up having to be treated at a non-VA facility last year.
Having the beeper numbers of my doctors makes me feel more secure. Susan always
returns my pages right away. I would prefer to set up the appointments only every 3
months and just be able to call in between.
24. Talking with and meeting with the provider about diet etc. should be done on an
immediate basis. "Very important at first." Appointments should be combined as
much as possible to avoid hardship to patients who do not live in Gainesville area.
25. Everything is fine. Keep up the good work.
26. Sometimes 1 would have more interest in other problems 1 have.
27. 1 am very satisfied with the service that I get.
28. Set up a blood check on Sunday for people who can't get here on weekdays - also
so they can get medication on that day. Nashville, TN can help your staff- check
out there program, it will help Vets get better treatment and cause less problems
- for everyone.
29. 1 would like to see someone closer to my home - such as the VA outpatient facility
in Tallahassee. It is very difficult for me to get to your clinic since my wife and I
are both in our seventies and have difficulty driving the long distance.
David Paul Nau was bom on March 17, 1966, in Toledo, Ohio. He received a
Bachelor of Science in Pharmacy degree from Ohio Northern University in 1989 and a
Master of Pharmaceutical Sciences degree from the University of Toledo in 1991. He
completed a general hospital residency at The Toledo Hospital in 1991 and a specialty
residency in hospital pharmacy administration at Shands Hospital at the University of
Florida in 1992. He served as supervisor of IV Therapy at Shands Hospital during 1992-
1993 before pursuing a doctoral degree in the Department of Pharmacy Health Care
Administration at the University of Florida. He is a recipient of the Lippman Fellowship
from the University of Florida College of Pharmacy and a member of Rho Chi Honorary
His research interests are centered around assessing and improving the quality of the
medication use system. This has included the development of innovative pharmacy
services for the chronically ill, evaluating the impact of these services on patients' quality
of life, and investigating patients' willingness to participate in pharmaceutical care.
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is folly adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
L. Douglas R(ed, Chair
Associate Proressor of
Pharmacy Health Care Administration
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is folly adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
Associate Professor of
Pharmacy Health Care Administration
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is folly adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
Pharmacy Health Care Administration
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is folly adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
J^ne Pendergast (j
Research Associate Professor
The dissertation was submitted to the Graduate Faculty of the College of
Pharmacy and to the Graduate School and was accept^^ a^ p^rti^l^'^^llrqeiy^f^
requirements for the degree of Doctor of Philosophy'
Dean, Graduate School
XmU NCI' ■ .' ■'/■■- i
UNIVERSITY OF FLORIDA
3 1262 08555 3179